{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2f52052a-eacc-4eae-b02b-831994208934",
   "metadata": {},
   "source": [
    "recreating fig 2 from 2021 Palmer et al. paper\n",
    "https://www.pnas.org/doi/abs/10.1073/pnas.2114326118?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub++0pubmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e07d9e36-bdcc-4fb5-9750-a2cd88d4b216",
   "metadata": {},
   "outputs": [],
   "source": [
    "library(Seurat)\n",
    "library(ggplot2)\n",
    "library(viridis)\n",
    "library(ComplexHeatmap)\n",
    "library(circlize)\n",
    "library(scCustomize)\n",
    "library(Rfast)\n",
    "library(reshape2)\n",
    "library(stringr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "391531a1-e11d-41d3-b72b-660b2f5f74f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "sobj <- readRDS(\"/tscc/projects/ps-epigen/users/kdang/ASAP/rds_objs/aging_merged_processed_v3_wwn_nodoub_v2_batch_cpeaks_batch_finalishWNN_frozenVersion_macs3peaks_chromvar_noATACassay.rds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "46279a71-f4d1-481f-8ce5-d6e6a75a31b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: Signac\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 41</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>orig.ident</th><th scope=col>nCount_RNA</th><th scope=col>nFeature_RNA</th><th scope=col>nCount_ATAC</th><th scope=col>nFeature_ATAC</th><th scope=col>percent.mt</th><th scope=col>nCount_SCT</th><th scope=col>nFeature_SCT</th><th scope=col>nCount_ATAC_COMB</th><th scope=col>nFeature_ATAC_COMB</th><th scope=col>⋯</th><th scope=col>cpeaks_snn_res.1.2</th><th scope=col>cpeaks.weight</th><th scope=col>broad_celltypes</th><th scope=col>sub_celltypes</th><th scope=col>sub_celltypes_v2</th><th scope=col>frozenBatch</th><th scope=col>nCount_macs3_peaks</th><th scope=col>nFeature_macs3_peaks</th><th scope=col>replicates</th><th scope=col>ct_cond</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>⋯</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1</th><td>QY_2139_1_2_QY_2138_1_2</td><td>29900</td><td>6204</td><td>26824</td><td>11160</td><td>0.70903010</td><td>4210</td><td>2107</td><td>17090</td><td>13408</td><td>⋯</td><td>3 </td><td>0.4232354</td><td>GABAergic    </td><td>GABAergic_NDB-SI-MA-STRv_Lhx8</td><td>GABAergic_Gbx1     </td><td>NotFrozen</td><td>17736</td><td>14692</td><td>Dp16_old_Rep1</td><td>GABAergic_Dp16_old    </td></tr>\n",
       "\t<tr><th scope=row>QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1</th><td>QY_2139_1_2_QY_2138_1_2</td><td>28031</td><td>6003</td><td>17321</td><td> 8077</td><td>0.30323570</td><td>4246</td><td>2117</td><td>11269</td><td> 9849</td><td>⋯</td><td>20</td><td>0.4709096</td><td>GABAergic    </td><td>GABAergic_STR_D1_Sema5a      </td><td>GABAergic_Mafa     </td><td>NotFrozen</td><td>11448</td><td>10294</td><td>Dp16_old_Rep1</td><td>GABAergic_Dp16_old    </td></tr>\n",
       "\t<tr><th scope=row>QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1</th><td>QY_2139_1_2_QY_2138_1_2</td><td>27880</td><td>6175</td><td>13896</td><td> 6636</td><td>0.21162123</td><td>4233</td><td>2121</td><td> 9156</td><td> 8029</td><td>⋯</td><td>5 </td><td>0.3567048</td><td>GABAergic    </td><td>GABAergic_Pvpo-VMPO-MPN_Hmx2 </td><td>GABAergic_Sox14    </td><td>NotFrozen</td><td> 9431</td><td> 8574</td><td>Dp16_old_Rep1</td><td>GABAergic_Dp16_old    </td></tr>\n",
       "\t<tr><th scope=row>QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1</th><td>QY_2139_1_2_QY_2138_1_2</td><td>26613</td><td>5747</td><td>47180</td><td>19500</td><td>0.09769661</td><td>4254</td><td>2081</td><td>32827</td><td>25276</td><td>⋯</td><td>14</td><td>0.3389017</td><td>GABAergic    </td><td>GABAergic_LSX_Prdm12_Slit2   </td><td>GABAergic_Kynu     </td><td>NotFrozen</td><td>33696</td><td>27894</td><td>Dp16_old_Rep1</td><td>GABAergic_Dp16_old    </td></tr>\n",
       "\t<tr><th scope=row>QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1</th><td>QY_2139_1_2_QY_2138_1_2</td><td>26487</td><td>6150</td><td>57216</td><td>23439</td><td>0.92498207</td><td>4272</td><td>2141</td><td>41919</td><td>31492</td><td>⋯</td><td>42</td><td>0.5711914</td><td>Glutamatergic</td><td>Glutamatergic_RE-Xi_Nox4     </td><td>Glutamatergic_Shox2</td><td>NotFrozen</td><td>45738</td><td>37512</td><td>Dp16_old_Rep1</td><td>Glutamatergic_Dp16_old</td></tr>\n",
       "\t<tr><th scope=row>QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1</th><td>QY_2139_1_2_QY_2138_1_2</td><td>26364</td><td>6024</td><td>38509</td><td>16232</td><td>0.25034137</td><td>4361</td><td>2219</td><td>27086</td><td>21090</td><td>⋯</td><td>26</td><td>0.4561977</td><td>GABAergic    </td><td>GABAergic_Vip                </td><td>GABAergic_Vip      </td><td>NotFrozen</td><td>28403</td><td>23689</td><td>Dp16_old_Rep1</td><td>GABAergic_Dp16_old    </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 41\n",
       "\\begin{tabular}{r|lllllllllllllllllllll}\n",
       "  & orig.ident & nCount\\_RNA & nFeature\\_RNA & nCount\\_ATAC & nFeature\\_ATAC & percent.mt & nCount\\_SCT & nFeature\\_SCT & nCount\\_ATAC\\_COMB & nFeature\\_ATAC\\_COMB & ⋯ & cpeaks\\_snn\\_res.1.2 & cpeaks.weight & broad\\_celltypes & sub\\_celltypes & sub\\_celltypes\\_v2 & frozenBatch & nCount\\_macs3\\_peaks & nFeature\\_macs3\\_peaks & replicates & ct\\_cond\\\\\n",
       "  & <chr> & <dbl> & <int> & <dbl> & <int> & <dbl> & <dbl> & <int> & <dbl> & <int> & ⋯ & <fct> & <dbl> & <fct> & <fct> & <fct> & <chr> & <dbl> & <int> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\tQY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2\\_TACTGCACAACACCTA-1 & QY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2 & 29900 & 6204 & 26824 & 11160 & 0.70903010 & 4210 & 2107 & 17090 & 13408 & ⋯ & 3  & 0.4232354 & GABAergic     & GABAergic\\_NDB-SI-MA-STRv\\_Lhx8 & GABAergic\\_Gbx1      & NotFrozen & 17736 & 14692 & Dp16\\_old\\_Rep1 & GABAergic\\_Dp16\\_old    \\\\\n",
       "\tQY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2\\_CAACCCGCACAAACTT-1 & QY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2 & 28031 & 6003 & 17321 &  8077 & 0.30323570 & 4246 & 2117 & 11269 &  9849 & ⋯ & 20 & 0.4709096 & GABAergic     & GABAergic\\_STR\\_D1\\_Sema5a       & GABAergic\\_Mafa      & NotFrozen & 11448 & 10294 & Dp16\\_old\\_Rep1 & GABAergic\\_Dp16\\_old    \\\\\n",
       "\tQY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2\\_TTAGACTCACCACAAC-1 & QY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2 & 27880 & 6175 & 13896 &  6636 & 0.21162123 & 4233 & 2121 &  9156 &  8029 & ⋯ & 5  & 0.3567048 & GABAergic     & GABAergic\\_Pvpo-VMPO-MPN\\_Hmx2  & GABAergic\\_Sox14     & NotFrozen &  9431 &  8574 & Dp16\\_old\\_Rep1 & GABAergic\\_Dp16\\_old    \\\\\n",
       "\tQY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2\\_TCATAACCATCAGCAC-1 & QY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2 & 26613 & 5747 & 47180 & 19500 & 0.09769661 & 4254 & 2081 & 32827 & 25276 & ⋯ & 14 & 0.3389017 & GABAergic     & GABAergic\\_LSX\\_Prdm12\\_Slit2    & GABAergic\\_Kynu      & NotFrozen & 33696 & 27894 & Dp16\\_old\\_Rep1 & GABAergic\\_Dp16\\_old    \\\\\n",
       "\tQY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2\\_TGACTCCTCGCTAGCA-1 & QY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2 & 26487 & 6150 & 57216 & 23439 & 0.92498207 & 4272 & 2141 & 41919 & 31492 & ⋯ & 42 & 0.5711914 & Glutamatergic & Glutamatergic\\_RE-Xi\\_Nox4      & Glutamatergic\\_Shox2 & NotFrozen & 45738 & 37512 & Dp16\\_old\\_Rep1 & Glutamatergic\\_Dp16\\_old\\\\\n",
       "\tQY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2\\_AAAGCTTGTCATCCTG-1 & QY\\_2139\\_1\\_2\\_QY\\_2138\\_1\\_2 & 26364 & 6024 & 38509 & 16232 & 0.25034137 & 4361 & 2219 & 27086 & 21090 & ⋯ & 26 & 0.4561977 & GABAergic     & GABAergic\\_Vip                 & GABAergic\\_Vip       & NotFrozen & 28403 & 23689 & Dp16\\_old\\_Rep1 & GABAergic\\_Dp16\\_old    \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 41\n",
       "\n",
       "| <!--/--> | orig.ident &lt;chr&gt; | nCount_RNA &lt;dbl&gt; | nFeature_RNA &lt;int&gt; | nCount_ATAC &lt;dbl&gt; | nFeature_ATAC &lt;int&gt; | percent.mt &lt;dbl&gt; | nCount_SCT &lt;dbl&gt; | nFeature_SCT &lt;int&gt; | nCount_ATAC_COMB &lt;dbl&gt; | nFeature_ATAC_COMB &lt;int&gt; | ⋯ ⋯ | cpeaks_snn_res.1.2 &lt;fct&gt; | cpeaks.weight &lt;dbl&gt; | broad_celltypes &lt;fct&gt; | sub_celltypes &lt;fct&gt; | sub_celltypes_v2 &lt;fct&gt; | frozenBatch &lt;chr&gt; | nCount_macs3_peaks &lt;dbl&gt; | nFeature_macs3_peaks &lt;int&gt; | replicates &lt;chr&gt; | ct_cond &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 | QY_2139_1_2_QY_2138_1_2 | 29900 | 6204 | 26824 | 11160 | 0.70903010 | 4210 | 2107 | 17090 | 13408 | ⋯ | 3  | 0.4232354 | GABAergic     | GABAergic_NDB-SI-MA-STRv_Lhx8 | GABAergic_Gbx1      | NotFrozen | 17736 | 14692 | Dp16_old_Rep1 | GABAergic_Dp16_old     |\n",
       "| QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 | QY_2139_1_2_QY_2138_1_2 | 28031 | 6003 | 17321 |  8077 | 0.30323570 | 4246 | 2117 | 11269 |  9849 | ⋯ | 20 | 0.4709096 | GABAergic     | GABAergic_STR_D1_Sema5a       | GABAergic_Mafa      | NotFrozen | 11448 | 10294 | Dp16_old_Rep1 | GABAergic_Dp16_old     |\n",
       "| QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 | QY_2139_1_2_QY_2138_1_2 | 27880 | 6175 | 13896 |  6636 | 0.21162123 | 4233 | 2121 |  9156 |  8029 | ⋯ | 5  | 0.3567048 | GABAergic     | GABAergic_Pvpo-VMPO-MPN_Hmx2  | GABAergic_Sox14     | NotFrozen |  9431 |  8574 | Dp16_old_Rep1 | GABAergic_Dp16_old     |\n",
       "| QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 | QY_2139_1_2_QY_2138_1_2 | 26613 | 5747 | 47180 | 19500 | 0.09769661 | 4254 | 2081 | 32827 | 25276 | ⋯ | 14 | 0.3389017 | GABAergic     | GABAergic_LSX_Prdm12_Slit2    | GABAergic_Kynu      | NotFrozen | 33696 | 27894 | Dp16_old_Rep1 | GABAergic_Dp16_old     |\n",
       "| QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 | QY_2139_1_2_QY_2138_1_2 | 26487 | 6150 | 57216 | 23439 | 0.92498207 | 4272 | 2141 | 41919 | 31492 | ⋯ | 42 | 0.5711914 | Glutamatergic | Glutamatergic_RE-Xi_Nox4      | Glutamatergic_Shox2 | NotFrozen | 45738 | 37512 | Dp16_old_Rep1 | Glutamatergic_Dp16_old |\n",
       "| QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 | QY_2139_1_2_QY_2138_1_2 | 26364 | 6024 | 38509 | 16232 | 0.25034137 | 4361 | 2219 | 27086 | 21090 | ⋯ | 26 | 0.4561977 | GABAergic     | GABAergic_Vip                 | GABAergic_Vip       | NotFrozen | 28403 | 23689 | Dp16_old_Rep1 | GABAergic_Dp16_old     |\n",
       "\n"
      ],
      "text/plain": [
       "                                           orig.ident              nCount_RNA\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 QY_2139_1_2_QY_2138_1_2 29900     \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 QY_2139_1_2_QY_2138_1_2 28031     \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 QY_2139_1_2_QY_2138_1_2 27880     \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 QY_2139_1_2_QY_2138_1_2 26613     \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 QY_2139_1_2_QY_2138_1_2 26487     \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 QY_2139_1_2_QY_2138_1_2 26364     \n",
       "                                           nFeature_RNA nCount_ATAC\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 6204         26824      \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 6003         17321      \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 6175         13896      \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 5747         47180      \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 6150         57216      \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 6024         38509      \n",
       "                                           nFeature_ATAC percent.mt nCount_SCT\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 11160         0.70903010 4210      \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1  8077         0.30323570 4246      \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1  6636         0.21162123 4233      \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 19500         0.09769661 4254      \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 23439         0.92498207 4272      \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 16232         0.25034137 4361      \n",
       "                                           nFeature_SCT nCount_ATAC_COMB\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 2107         17090           \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 2117         11269           \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 2121          9156           \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 2081         32827           \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 2141         41919           \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 2219         27086           \n",
       "                                           nFeature_ATAC_COMB ⋯\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 13408              ⋯\n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1  9849              ⋯\n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1  8029              ⋯\n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 25276              ⋯\n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 31492              ⋯\n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 21090              ⋯\n",
       "                                           cpeaks_snn_res.1.2 cpeaks.weight\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 3                  0.4232354    \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 20                 0.4709096    \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 5                  0.3567048    \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 14                 0.3389017    \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 42                 0.5711914    \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 26                 0.4561977    \n",
       "                                           broad_celltypes\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 GABAergic      \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 GABAergic      \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 GABAergic      \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 GABAergic      \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 Glutamatergic  \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 GABAergic      \n",
       "                                           sub_celltypes                \n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 GABAergic_NDB-SI-MA-STRv_Lhx8\n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 GABAergic_STR_D1_Sema5a      \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 GABAergic_Pvpo-VMPO-MPN_Hmx2 \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 GABAergic_LSX_Prdm12_Slit2   \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 Glutamatergic_RE-Xi_Nox4     \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 GABAergic_Vip                \n",
       "                                           sub_celltypes_v2    frozenBatch\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 GABAergic_Gbx1      NotFrozen  \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 GABAergic_Mafa      NotFrozen  \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 GABAergic_Sox14     NotFrozen  \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 GABAergic_Kynu      NotFrozen  \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 Glutamatergic_Shox2 NotFrozen  \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 GABAergic_Vip       NotFrozen  \n",
       "                                           nCount_macs3_peaks\n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 17736             \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 11448             \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1  9431             \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 33696             \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 45738             \n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 28403             \n",
       "                                           nFeature_macs3_peaks replicates   \n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 14692                Dp16_old_Rep1\n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 10294                Dp16_old_Rep1\n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1  8574                Dp16_old_Rep1\n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 27894                Dp16_old_Rep1\n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 37512                Dp16_old_Rep1\n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 23689                Dp16_old_Rep1\n",
       "                                           ct_cond               \n",
       "QY_2139_1_2_QY_2138_1_2_TACTGCACAACACCTA-1 GABAergic_Dp16_old    \n",
       "QY_2139_1_2_QY_2138_1_2_CAACCCGCACAAACTT-1 GABAergic_Dp16_old    \n",
       "QY_2139_1_2_QY_2138_1_2_TTAGACTCACCACAAC-1 GABAergic_Dp16_old    \n",
       "QY_2139_1_2_QY_2138_1_2_TCATAACCATCAGCAC-1 GABAergic_Dp16_old    \n",
       "QY_2139_1_2_QY_2138_1_2_TGACTCCTCGCTAGCA-1 Glutamatergic_Dp16_old\n",
       "QY_2139_1_2_QY_2138_1_2_AAAGCTTGTCATCCTG-1 GABAergic_Dp16_old    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# add in metacol with celltype and condition combined bc split.by in dotplot removes the average expression from legend\n",
    "sobj$ct_cond <- paste0(sobj$broad_celltypes, \"_\", sobj$conditions)\n",
    "\n",
    "head(sobj@meta.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b2f82fc4-6b4c-4ff2-8cd1-e99c287e5b62",
   "metadata": {},
   "outputs": [],
   "source": [
    "sobj_nodoub <- subset(sobj, subset = broad_celltypes == \"Doublet\", invert = TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "09fd03b0-5aa1-4d88-ac25-653679177230",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "An object of class Seurat \n",
       "975987 features across 91091 samples within 5 assays \n",
       "Active assay: cpeaks (478426 features, 478426 variable features)\n",
       " 2 layers present: counts, data\n",
       " 4 other assays present: RNA, SCT, macs3_peaks, chromvar\n",
       " 9 dimensional reductions calculated: pca, harmony, umap, harmony.rna, umap.hrm.rna, lsi, harmony.atac, umap.hrm.atac, umap.hrm.wnn"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'orig.ident'</li><li>'nCount_RNA'</li><li>'nFeature_RNA'</li><li>'nCount_ATAC'</li><li>'nFeature_ATAC'</li><li>'percent.mt'</li><li>'nCount_SCT'</li><li>'nFeature_SCT'</li><li>'nCount_ATAC_COMB'</li><li>'nFeature_ATAC_COMB'</li><li>'SCT_snn_res.0.5'</li><li>'seurat_clusters'</li><li>'conditions'</li><li>'SCT_snn_res.0.05'</li><li>'TSS.enrichment'</li><li>'TSS.percentile'</li><li>'DF.classification'</li><li>'DF.scores'</li><li>'age'</li><li>'genotype'</li><li>'blacklist_fraction'</li><li>'SCT_snn_res.1.2'</li><li>'ATAC_snn_res.1.2'</li><li>'SCT.weight'</li><li>'ATAC.weight'</li><li>'wsnn_res.1.2'</li><li>'qn.DF.scores'</li><li>'ATAC_COMB_snn_res.1.2'</li><li>'ATAC_COMB.weight'</li><li>'nCount_cpeaks'</li><li>'nFeature_cpeaks'</li><li>'cpeaks_snn_res.1.2'</li><li>'cpeaks.weight'</li><li>'broad_celltypes'</li><li>'sub_celltypes'</li><li>'sub_celltypes_v2'</li><li>'frozenBatch'</li><li>'nCount_macs3_peaks'</li><li>'nFeature_macs3_peaks'</li><li>'replicates'</li><li>'ct_cond'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'orig.ident'\n",
       "\\item 'nCount\\_RNA'\n",
       "\\item 'nFeature\\_RNA'\n",
       "\\item 'nCount\\_ATAC'\n",
       "\\item 'nFeature\\_ATAC'\n",
       "\\item 'percent.mt'\n",
       "\\item 'nCount\\_SCT'\n",
       "\\item 'nFeature\\_SCT'\n",
       "\\item 'nCount\\_ATAC\\_COMB'\n",
       "\\item 'nFeature\\_ATAC\\_COMB'\n",
       "\\item 'SCT\\_snn\\_res.0.5'\n",
       "\\item 'seurat\\_clusters'\n",
       "\\item 'conditions'\n",
       "\\item 'SCT\\_snn\\_res.0.05'\n",
       "\\item 'TSS.enrichment'\n",
       "\\item 'TSS.percentile'\n",
       "\\item 'DF.classification'\n",
       "\\item 'DF.scores'\n",
       "\\item 'age'\n",
       "\\item 'genotype'\n",
       "\\item 'blacklist\\_fraction'\n",
       "\\item 'SCT\\_snn\\_res.1.2'\n",
       "\\item 'ATAC\\_snn\\_res.1.2'\n",
       "\\item 'SCT.weight'\n",
       "\\item 'ATAC.weight'\n",
       "\\item 'wsnn\\_res.1.2'\n",
       "\\item 'qn.DF.scores'\n",
       "\\item 'ATAC\\_COMB\\_snn\\_res.1.2'\n",
       "\\item 'ATAC\\_COMB.weight'\n",
       "\\item 'nCount\\_cpeaks'\n",
       "\\item 'nFeature\\_cpeaks'\n",
       "\\item 'cpeaks\\_snn\\_res.1.2'\n",
       "\\item 'cpeaks.weight'\n",
       "\\item 'broad\\_celltypes'\n",
       "\\item 'sub\\_celltypes'\n",
       "\\item 'sub\\_celltypes\\_v2'\n",
       "\\item 'frozenBatch'\n",
       "\\item 'nCount\\_macs3\\_peaks'\n",
       "\\item 'nFeature\\_macs3\\_peaks'\n",
       "\\item 'replicates'\n",
       "\\item 'ct\\_cond'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'orig.ident'\n",
       "2. 'nCount_RNA'\n",
       "3. 'nFeature_RNA'\n",
       "4. 'nCount_ATAC'\n",
       "5. 'nFeature_ATAC'\n",
       "6. 'percent.mt'\n",
       "7. 'nCount_SCT'\n",
       "8. 'nFeature_SCT'\n",
       "9. 'nCount_ATAC_COMB'\n",
       "10. 'nFeature_ATAC_COMB'\n",
       "11. 'SCT_snn_res.0.5'\n",
       "12. 'seurat_clusters'\n",
       "13. 'conditions'\n",
       "14. 'SCT_snn_res.0.05'\n",
       "15. 'TSS.enrichment'\n",
       "16. 'TSS.percentile'\n",
       "17. 'DF.classification'\n",
       "18. 'DF.scores'\n",
       "19. 'age'\n",
       "20. 'genotype'\n",
       "21. 'blacklist_fraction'\n",
       "22. 'SCT_snn_res.1.2'\n",
       "23. 'ATAC_snn_res.1.2'\n",
       "24. 'SCT.weight'\n",
       "25. 'ATAC.weight'\n",
       "26. 'wsnn_res.1.2'\n",
       "27. 'qn.DF.scores'\n",
       "28. 'ATAC_COMB_snn_res.1.2'\n",
       "29. 'ATAC_COMB.weight'\n",
       "30. 'nCount_cpeaks'\n",
       "31. 'nFeature_cpeaks'\n",
       "32. 'cpeaks_snn_res.1.2'\n",
       "33. 'cpeaks.weight'\n",
       "34. 'broad_celltypes'\n",
       "35. 'sub_celltypes'\n",
       "36. 'sub_celltypes_v2'\n",
       "37. 'frozenBatch'\n",
       "38. 'nCount_macs3_peaks'\n",
       "39. 'nFeature_macs3_peaks'\n",
       "40. 'replicates'\n",
       "41. 'ct_cond'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"orig.ident\"            \"nCount_RNA\"            \"nFeature_RNA\"         \n",
       " [4] \"nCount_ATAC\"           \"nFeature_ATAC\"         \"percent.mt\"           \n",
       " [7] \"nCount_SCT\"            \"nFeature_SCT\"          \"nCount_ATAC_COMB\"     \n",
       "[10] \"nFeature_ATAC_COMB\"    \"SCT_snn_res.0.5\"       \"seurat_clusters\"      \n",
       "[13] \"conditions\"            \"SCT_snn_res.0.05\"      \"TSS.enrichment\"       \n",
       "[16] \"TSS.percentile\"        \"DF.classification\"     \"DF.scores\"            \n",
       "[19] \"age\"                   \"genotype\"              \"blacklist_fraction\"   \n",
       "[22] \"SCT_snn_res.1.2\"       \"ATAC_snn_res.1.2\"      \"SCT.weight\"           \n",
       "[25] \"ATAC.weight\"           \"wsnn_res.1.2\"          \"qn.DF.scores\"         \n",
       "[28] \"ATAC_COMB_snn_res.1.2\" \"ATAC_COMB.weight\"      \"nCount_cpeaks\"        \n",
       "[31] \"nFeature_cpeaks\"       \"cpeaks_snn_res.1.2\"    \"cpeaks.weight\"        \n",
       "[34] \"broad_celltypes\"       \"sub_celltypes\"         \"sub_celltypes_v2\"     \n",
       "[37] \"frozenBatch\"           \"nCount_macs3_peaks\"    \"nFeature_macs3_peaks\" \n",
       "[40] \"replicates\"            \"ct_cond\"              "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>GABAergic</li><li>Glutamatergic</li><li>BFCN</li><li>OPC</li><li>Doublet</li><li>Oligodendrocyte</li><li>Astrocyte</li><li>Microglia</li></ol>\n",
       "\n",
       "<details>\n",
       "\t<summary style=display:list-item;cursor:pointer>\n",
       "\t\t<strong>Levels</strong>:\n",
       "\t</summary>\n",
       "\t<style>\n",
       "\t.list-inline {list-style: none; margin:0; padding: 0}\n",
       "\t.list-inline>li {display: inline-block}\n",
       "\t.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "\t</style>\n",
       "\t<ol class=list-inline><li>'Astrocyte'</li><li>'Microglia'</li><li>'Oligodendrocyte'</li><li>'OPC'</li><li>'BFCN'</li><li>'GABAergic'</li><li>'Glutamatergic'</li><li>'Doublet'</li></ol>\n",
       "</details>"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item GABAergic\n",
       "\\item Glutamatergic\n",
       "\\item BFCN\n",
       "\\item OPC\n",
       "\\item Doublet\n",
       "\\item Oligodendrocyte\n",
       "\\item Astrocyte\n",
       "\\item Microglia\n",
       "\\end{enumerate*}\n",
       "\n",
       "\\emph{Levels}: \\begin{enumerate*}\n",
       "\\item 'Astrocyte'\n",
       "\\item 'Microglia'\n",
       "\\item 'Oligodendrocyte'\n",
       "\\item 'OPC'\n",
       "\\item 'BFCN'\n",
       "\\item 'GABAergic'\n",
       "\\item 'Glutamatergic'\n",
       "\\item 'Doublet'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. GABAergic\n",
       "2. Glutamatergic\n",
       "3. BFCN\n",
       "4. OPC\n",
       "5. Doublet\n",
       "6. Oligodendrocyte\n",
       "7. Astrocyte\n",
       "8. Microglia\n",
       "\n",
       "\n",
       "\n",
       "**Levels**: 1. 'Astrocyte'\n",
       "2. 'Microglia'\n",
       "3. 'Oligodendrocyte'\n",
       "4. 'OPC'\n",
       "5. 'BFCN'\n",
       "6. 'GABAergic'\n",
       "7. 'Glutamatergic'\n",
       "8. 'Doublet'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] GABAergic       Glutamatergic   BFCN            OPC            \n",
       "[5] Doublet         Oligodendrocyte Astrocyte       Microglia      \n",
       "8 Levels: Astrocyte Microglia Oligodendrocyte OPC BFCN ... Doublet"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "An object of class Seurat \n",
       "975987 features across 89812 samples within 5 assays \n",
       "Active assay: cpeaks (478426 features, 478426 variable features)\n",
       " 2 layers present: counts, data\n",
       " 4 other assays present: RNA, SCT, macs3_peaks, chromvar\n",
       " 9 dimensional reductions calculated: pca, harmony, umap, harmony.rna, umap.hrm.rna, lsi, harmony.atac, umap.hrm.atac, umap.hrm.wnn"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'orig.ident'</li><li>'nCount_RNA'</li><li>'nFeature_RNA'</li><li>'nCount_ATAC'</li><li>'nFeature_ATAC'</li><li>'percent.mt'</li><li>'nCount_SCT'</li><li>'nFeature_SCT'</li><li>'nCount_ATAC_COMB'</li><li>'nFeature_ATAC_COMB'</li><li>'SCT_snn_res.0.5'</li><li>'seurat_clusters'</li><li>'conditions'</li><li>'SCT_snn_res.0.05'</li><li>'TSS.enrichment'</li><li>'TSS.percentile'</li><li>'DF.classification'</li><li>'DF.scores'</li><li>'age'</li><li>'genotype'</li><li>'blacklist_fraction'</li><li>'SCT_snn_res.1.2'</li><li>'ATAC_snn_res.1.2'</li><li>'SCT.weight'</li><li>'ATAC.weight'</li><li>'wsnn_res.1.2'</li><li>'qn.DF.scores'</li><li>'ATAC_COMB_snn_res.1.2'</li><li>'ATAC_COMB.weight'</li><li>'nCount_cpeaks'</li><li>'nFeature_cpeaks'</li><li>'cpeaks_snn_res.1.2'</li><li>'cpeaks.weight'</li><li>'broad_celltypes'</li><li>'sub_celltypes'</li><li>'sub_celltypes_v2'</li><li>'frozenBatch'</li><li>'nCount_macs3_peaks'</li><li>'nFeature_macs3_peaks'</li><li>'replicates'</li><li>'ct_cond'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'orig.ident'\n",
       "\\item 'nCount\\_RNA'\n",
       "\\item 'nFeature\\_RNA'\n",
       "\\item 'nCount\\_ATAC'\n",
       "\\item 'nFeature\\_ATAC'\n",
       "\\item 'percent.mt'\n",
       "\\item 'nCount\\_SCT'\n",
       "\\item 'nFeature\\_SCT'\n",
       "\\item 'nCount\\_ATAC\\_COMB'\n",
       "\\item 'nFeature\\_ATAC\\_COMB'\n",
       "\\item 'SCT\\_snn\\_res.0.5'\n",
       "\\item 'seurat\\_clusters'\n",
       "\\item 'conditions'\n",
       "\\item 'SCT\\_snn\\_res.0.05'\n",
       "\\item 'TSS.enrichment'\n",
       "\\item 'TSS.percentile'\n",
       "\\item 'DF.classification'\n",
       "\\item 'DF.scores'\n",
       "\\item 'age'\n",
       "\\item 'genotype'\n",
       "\\item 'blacklist\\_fraction'\n",
       "\\item 'SCT\\_snn\\_res.1.2'\n",
       "\\item 'ATAC\\_snn\\_res.1.2'\n",
       "\\item 'SCT.weight'\n",
       "\\item 'ATAC.weight'\n",
       "\\item 'wsnn\\_res.1.2'\n",
       "\\item 'qn.DF.scores'\n",
       "\\item 'ATAC\\_COMB\\_snn\\_res.1.2'\n",
       "\\item 'ATAC\\_COMB.weight'\n",
       "\\item 'nCount\\_cpeaks'\n",
       "\\item 'nFeature\\_cpeaks'\n",
       "\\item 'cpeaks\\_snn\\_res.1.2'\n",
       "\\item 'cpeaks.weight'\n",
       "\\item 'broad\\_celltypes'\n",
       "\\item 'sub\\_celltypes'\n",
       "\\item 'sub\\_celltypes\\_v2'\n",
       "\\item 'frozenBatch'\n",
       "\\item 'nCount\\_macs3\\_peaks'\n",
       "\\item 'nFeature\\_macs3\\_peaks'\n",
       "\\item 'replicates'\n",
       "\\item 'ct\\_cond'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'orig.ident'\n",
       "2. 'nCount_RNA'\n",
       "3. 'nFeature_RNA'\n",
       "4. 'nCount_ATAC'\n",
       "5. 'nFeature_ATAC'\n",
       "6. 'percent.mt'\n",
       "7. 'nCount_SCT'\n",
       "8. 'nFeature_SCT'\n",
       "9. 'nCount_ATAC_COMB'\n",
       "10. 'nFeature_ATAC_COMB'\n",
       "11. 'SCT_snn_res.0.5'\n",
       "12. 'seurat_clusters'\n",
       "13. 'conditions'\n",
       "14. 'SCT_snn_res.0.05'\n",
       "15. 'TSS.enrichment'\n",
       "16. 'TSS.percentile'\n",
       "17. 'DF.classification'\n",
       "18. 'DF.scores'\n",
       "19. 'age'\n",
       "20. 'genotype'\n",
       "21. 'blacklist_fraction'\n",
       "22. 'SCT_snn_res.1.2'\n",
       "23. 'ATAC_snn_res.1.2'\n",
       "24. 'SCT.weight'\n",
       "25. 'ATAC.weight'\n",
       "26. 'wsnn_res.1.2'\n",
       "27. 'qn.DF.scores'\n",
       "28. 'ATAC_COMB_snn_res.1.2'\n",
       "29. 'ATAC_COMB.weight'\n",
       "30. 'nCount_cpeaks'\n",
       "31. 'nFeature_cpeaks'\n",
       "32. 'cpeaks_snn_res.1.2'\n",
       "33. 'cpeaks.weight'\n",
       "34. 'broad_celltypes'\n",
       "35. 'sub_celltypes'\n",
       "36. 'sub_celltypes_v2'\n",
       "37. 'frozenBatch'\n",
       "38. 'nCount_macs3_peaks'\n",
       "39. 'nFeature_macs3_peaks'\n",
       "40. 'replicates'\n",
       "41. 'ct_cond'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"orig.ident\"            \"nCount_RNA\"            \"nFeature_RNA\"         \n",
       " [4] \"nCount_ATAC\"           \"nFeature_ATAC\"         \"percent.mt\"           \n",
       " [7] \"nCount_SCT\"            \"nFeature_SCT\"          \"nCount_ATAC_COMB\"     \n",
       "[10] \"nFeature_ATAC_COMB\"    \"SCT_snn_res.0.5\"       \"seurat_clusters\"      \n",
       "[13] \"conditions\"            \"SCT_snn_res.0.05\"      \"TSS.enrichment\"       \n",
       "[16] \"TSS.percentile\"        \"DF.classification\"     \"DF.scores\"            \n",
       "[19] \"age\"                   \"genotype\"              \"blacklist_fraction\"   \n",
       "[22] \"SCT_snn_res.1.2\"       \"ATAC_snn_res.1.2\"      \"SCT.weight\"           \n",
       "[25] \"ATAC.weight\"           \"wsnn_res.1.2\"          \"qn.DF.scores\"         \n",
       "[28] \"ATAC_COMB_snn_res.1.2\" \"ATAC_COMB.weight\"      \"nCount_cpeaks\"        \n",
       "[31] \"nFeature_cpeaks\"       \"cpeaks_snn_res.1.2\"    \"cpeaks.weight\"        \n",
       "[34] \"broad_celltypes\"       \"sub_celltypes\"         \"sub_celltypes_v2\"     \n",
       "[37] \"frozenBatch\"           \"nCount_macs3_peaks\"    \"nFeature_macs3_peaks\" \n",
       "[40] \"replicates\"            \"ct_cond\"              "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sobj\n",
    "colnames(sobj@meta.data)\n",
    "unique(sobj$broad_celltypes)\n",
    "\n",
    "sobj_nodoub\n",
    "colnames(sobj_nodoub@meta.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95280bcc-b757-47ee-97b8-d66173456968",
   "metadata": {},
   "source": [
    "# fig 2b - heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "24fc8726-1a5a-4c56-a953-4d948e77d65a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Lipi'</li><li>'Rbm11'</li><li>'Hspa13'</li><li>'Samsn1'</li><li>'Nrip1'</li><li>'Usp25'</li><li>'mmu-miR-99a'</li><li>'mmu-let-7c-1'</li><li>'mmu-miR-125b-2'</li><li>'Cxadr'</li><li>'Btg3'</li><li>'D16Ertd472e'</li><li>'Chodl'</li><li>'Prss7'</li><li>'Ncam2'</li><li>'mmu-miR-155'</li><li>'Mrpl39'</li><li>'Jam2'</li><li>'Atp5j'</li><li>'Gabpa'</li><li>'App'</li><li>'Cyyr1'</li><li>'Adamts1'</li><li>'Adamts5'</li><li>'N6amt1'</li><li>'Zfp294'</li><li>'Rwdd2b'</li><li>'Usp16'</li><li>'Cct8'</li><li>'Orf63'</li><li>'Bach1'</li><li>'Grik1'</li><li>'Cldn17'</li><li>'Cldn8'</li><li>'Gm312'</li><li>'Krtap26-1'</li><li>'Krtap13-1'</li><li>'Krtap13'</li><li>'Krtap16'</li><li>'Krtap16-7'</li><li>'Krtap8-1'</li><li>'Tiam1'</li><li>'Krtap16-4'</li><li>'Krtap8-2'</li><li>'Sod1'</li><li>'Sfrs15'</li><li>'Hunk'</li><li>'2610039C10Rik'</li><li>'Mrap'</li><li>'Urb1'</li><li>'4931408A02Rik'</li><li>'1110004E09Rik'</li><li>'Synj1'</li><li>'1810007M14Rik'</li><li>'4932438H23Rik'</li><li>'Olig2'</li><li>'Olig1'</li><li>'Ifnar2'</li><li>'Il10rb'</li><li>'Ifnar1'</li><li>'Ifngr2'</li><li>'Tmem50b'</li><li>'Dnajc28'</li><li>'Gart'</li><li>'Son'</li><li>'Donson'</li><li>'Atp5o'</li><li>'Cryzl1'</li><li>'Itsn1'</li><li>'Mrps6'</li><li>'Slc5a3'</li><li>'Kcne2'</li><li>'4930563D23Rik'</li><li>'Kcne1'</li><li>'Rcan1'</li><li>'Clic6'</li><li>'Runx1'</li><li>'mmu-miR-802'</li><li>'Setd4'</li><li>'Cbr1'</li><li>'Cbr3'</li><li>'Dopey2'</li><li>'Morc3'</li><li>'Chaf1b'</li><li>'Cldn14'</li><li>'Sim2'</li><li>'Hlcs'</li><li>'Ripply3'</li><li>'Pigp'</li><li>'Ttc3'</li><li>'Dscr3'</li><li>'Dyrk1a'</li><li>'Kcnj6'</li><li>'Kcnj15'</li><li>'Erg'</li><li>'Ets2'</li><li>'Psmg1'</li><li>'Brwd1'</li><li>'Hmgn1'</li><li>'Wrb'</li><li>'Lca5l'</li><li>'Sh3bgr'</li><li>'B3galt5'</li><li>'Igsf5'</li><li>'Itgb2l'</li><li>'Dscam'</li><li>'Bace2'</li><li>'Fam3b'</li><li>'Mx2'</li><li>'Tmprss2'</li><li>'Ripk4'</li><li>'Prdm15'</li><li>'5830404H04Rik'</li><li>'Zfp295'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Lipi'\n",
       "\\item 'Rbm11'\n",
       "\\item 'Hspa13'\n",
       "\\item 'Samsn1'\n",
       "\\item 'Nrip1'\n",
       "\\item 'Usp25'\n",
       "\\item 'mmu-miR-99a'\n",
       "\\item 'mmu-let-7c-1'\n",
       "\\item 'mmu-miR-125b-2'\n",
       "\\item 'Cxadr'\n",
       "\\item 'Btg3'\n",
       "\\item 'D16Ertd472e'\n",
       "\\item 'Chodl'\n",
       "\\item 'Prss7'\n",
       "\\item 'Ncam2'\n",
       "\\item 'mmu-miR-155'\n",
       "\\item 'Mrpl39'\n",
       "\\item 'Jam2'\n",
       "\\item 'Atp5j'\n",
       "\\item 'Gabpa'\n",
       "\\item 'App'\n",
       "\\item 'Cyyr1'\n",
       "\\item 'Adamts1'\n",
       "\\item 'Adamts5'\n",
       "\\item 'N6amt1'\n",
       "\\item 'Zfp294'\n",
       "\\item 'Rwdd2b'\n",
       "\\item 'Usp16'\n",
       "\\item 'Cct8'\n",
       "\\item 'Orf63'\n",
       "\\item 'Bach1'\n",
       "\\item 'Grik1'\n",
       "\\item 'Cldn17'\n",
       "\\item 'Cldn8'\n",
       "\\item 'Gm312'\n",
       "\\item 'Krtap26-1'\n",
       "\\item 'Krtap13-1'\n",
       "\\item 'Krtap13'\n",
       "\\item 'Krtap16'\n",
       "\\item 'Krtap16-7'\n",
       "\\item 'Krtap8-1'\n",
       "\\item 'Tiam1'\n",
       "\\item 'Krtap16-4'\n",
       "\\item 'Krtap8-2'\n",
       "\\item 'Sod1'\n",
       "\\item 'Sfrs15'\n",
       "\\item 'Hunk'\n",
       "\\item '2610039C10Rik'\n",
       "\\item 'Mrap'\n",
       "\\item 'Urb1'\n",
       "\\item '4931408A02Rik'\n",
       "\\item '1110004E09Rik'\n",
       "\\item 'Synj1'\n",
       "\\item '1810007M14Rik'\n",
       "\\item '4932438H23Rik'\n",
       "\\item 'Olig2'\n",
       "\\item 'Olig1'\n",
       "\\item 'Ifnar2'\n",
       "\\item 'Il10rb'\n",
       "\\item 'Ifnar1'\n",
       "\\item 'Ifngr2'\n",
       "\\item 'Tmem50b'\n",
       "\\item 'Dnajc28'\n",
       "\\item 'Gart'\n",
       "\\item 'Son'\n",
       "\\item 'Donson'\n",
       "\\item 'Atp5o'\n",
       "\\item 'Cryzl1'\n",
       "\\item 'Itsn1'\n",
       "\\item 'Mrps6'\n",
       "\\item 'Slc5a3'\n",
       "\\item 'Kcne2'\n",
       "\\item '4930563D23Rik'\n",
       "\\item 'Kcne1'\n",
       "\\item 'Rcan1'\n",
       "\\item 'Clic6'\n",
       "\\item 'Runx1'\n",
       "\\item 'mmu-miR-802'\n",
       "\\item 'Setd4'\n",
       "\\item 'Cbr1'\n",
       "\\item 'Cbr3'\n",
       "\\item 'Dopey2'\n",
       "\\item 'Morc3'\n",
       "\\item 'Chaf1b'\n",
       "\\item 'Cldn14'\n",
       "\\item 'Sim2'\n",
       "\\item 'Hlcs'\n",
       "\\item 'Ripply3'\n",
       "\\item 'Pigp'\n",
       "\\item 'Ttc3'\n",
       "\\item 'Dscr3'\n",
       "\\item 'Dyrk1a'\n",
       "\\item 'Kcnj6'\n",
       "\\item 'Kcnj15'\n",
       "\\item 'Erg'\n",
       "\\item 'Ets2'\n",
       "\\item 'Psmg1'\n",
       "\\item 'Brwd1'\n",
       "\\item 'Hmgn1'\n",
       "\\item 'Wrb'\n",
       "\\item 'Lca5l'\n",
       "\\item 'Sh3bgr'\n",
       "\\item 'B3galt5'\n",
       "\\item 'Igsf5'\n",
       "\\item 'Itgb2l'\n",
       "\\item 'Dscam'\n",
       "\\item 'Bace2'\n",
       "\\item 'Fam3b'\n",
       "\\item 'Mx2'\n",
       "\\item 'Tmprss2'\n",
       "\\item 'Ripk4'\n",
       "\\item 'Prdm15'\n",
       "\\item '5830404H04Rik'\n",
       "\\item 'Zfp295'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Lipi'\n",
       "2. 'Rbm11'\n",
       "3. 'Hspa13'\n",
       "4. 'Samsn1'\n",
       "5. 'Nrip1'\n",
       "6. 'Usp25'\n",
       "7. 'mmu-miR-99a'\n",
       "8. 'mmu-let-7c-1'\n",
       "9. 'mmu-miR-125b-2'\n",
       "10. 'Cxadr'\n",
       "11. 'Btg3'\n",
       "12. 'D16Ertd472e'\n",
       "13. 'Chodl'\n",
       "14. 'Prss7'\n",
       "15. 'Ncam2'\n",
       "16. 'mmu-miR-155'\n",
       "17. 'Mrpl39'\n",
       "18. 'Jam2'\n",
       "19. 'Atp5j'\n",
       "20. 'Gabpa'\n",
       "21. 'App'\n",
       "22. 'Cyyr1'\n",
       "23. 'Adamts1'\n",
       "24. 'Adamts5'\n",
       "25. 'N6amt1'\n",
       "26. 'Zfp294'\n",
       "27. 'Rwdd2b'\n",
       "28. 'Usp16'\n",
       "29. 'Cct8'\n",
       "30. 'Orf63'\n",
       "31. 'Bach1'\n",
       "32. 'Grik1'\n",
       "33. 'Cldn17'\n",
       "34. 'Cldn8'\n",
       "35. 'Gm312'\n",
       "36. 'Krtap26-1'\n",
       "37. 'Krtap13-1'\n",
       "38. 'Krtap13'\n",
       "39. 'Krtap16'\n",
       "40. 'Krtap16-7'\n",
       "41. 'Krtap8-1'\n",
       "42. 'Tiam1'\n",
       "43. 'Krtap16-4'\n",
       "44. 'Krtap8-2'\n",
       "45. 'Sod1'\n",
       "46. 'Sfrs15'\n",
       "47. 'Hunk'\n",
       "48. '2610039C10Rik'\n",
       "49. 'Mrap'\n",
       "50. 'Urb1'\n",
       "51. '4931408A02Rik'\n",
       "52. '1110004E09Rik'\n",
       "53. 'Synj1'\n",
       "54. '1810007M14Rik'\n",
       "55. '4932438H23Rik'\n",
       "56. 'Olig2'\n",
       "57. 'Olig1'\n",
       "58. 'Ifnar2'\n",
       "59. 'Il10rb'\n",
       "60. 'Ifnar1'\n",
       "61. 'Ifngr2'\n",
       "62. 'Tmem50b'\n",
       "63. 'Dnajc28'\n",
       "64. 'Gart'\n",
       "65. 'Son'\n",
       "66. 'Donson'\n",
       "67. 'Atp5o'\n",
       "68. 'Cryzl1'\n",
       "69. 'Itsn1'\n",
       "70. 'Mrps6'\n",
       "71. 'Slc5a3'\n",
       "72. 'Kcne2'\n",
       "73. '4930563D23Rik'\n",
       "74. 'Kcne1'\n",
       "75. 'Rcan1'\n",
       "76. 'Clic6'\n",
       "77. 'Runx1'\n",
       "78. 'mmu-miR-802'\n",
       "79. 'Setd4'\n",
       "80. 'Cbr1'\n",
       "81. 'Cbr3'\n",
       "82. 'Dopey2'\n",
       "83. 'Morc3'\n",
       "84. 'Chaf1b'\n",
       "85. 'Cldn14'\n",
       "86. 'Sim2'\n",
       "87. 'Hlcs'\n",
       "88. 'Ripply3'\n",
       "89. 'Pigp'\n",
       "90. 'Ttc3'\n",
       "91. 'Dscr3'\n",
       "92. 'Dyrk1a'\n",
       "93. 'Kcnj6'\n",
       "94. 'Kcnj15'\n",
       "95. 'Erg'\n",
       "96. 'Ets2'\n",
       "97. 'Psmg1'\n",
       "98. 'Brwd1'\n",
       "99. 'Hmgn1'\n",
       "100. 'Wrb'\n",
       "101. 'Lca5l'\n",
       "102. 'Sh3bgr'\n",
       "103. 'B3galt5'\n",
       "104. 'Igsf5'\n",
       "105. 'Itgb2l'\n",
       "106. 'Dscam'\n",
       "107. 'Bace2'\n",
       "108. 'Fam3b'\n",
       "109. 'Mx2'\n",
       "110. 'Tmprss2'\n",
       "111. 'Ripk4'\n",
       "112. 'Prdm15'\n",
       "113. '5830404H04Rik'\n",
       "114. 'Zfp295'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  [1] \"Lipi\"           \"Rbm11\"          \"Hspa13\"         \"Samsn1\"        \n",
       "  [5] \"Nrip1\"          \"Usp25\"          \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
       "  [9] \"mmu-miR-125b-2\" \"Cxadr\"          \"Btg3\"           \"D16Ertd472e\"   \n",
       " [13] \"Chodl\"          \"Prss7\"          \"Ncam2\"          \"mmu-miR-155\"   \n",
       " [17] \"Mrpl39\"         \"Jam2\"           \"Atp5j\"          \"Gabpa\"         \n",
       " [21] \"App\"            \"Cyyr1\"          \"Adamts1\"        \"Adamts5\"       \n",
       " [25] \"N6amt1\"         \"Zfp294\"         \"Rwdd2b\"         \"Usp16\"         \n",
       " [29] \"Cct8\"           \"Orf63\"          \"Bach1\"          \"Grik1\"         \n",
       " [33] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
       " [37] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
       " [41] \"Krtap8-1\"       \"Tiam1\"          \"Krtap16-4\"      \"Krtap8-2\"      \n",
       " [45] \"Sod1\"           \"Sfrs15\"         \"Hunk\"           \"2610039C10Rik\" \n",
       " [49] \"Mrap\"           \"Urb1\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
       " [53] \"Synj1\"          \"1810007M14Rik\"  \"4932438H23Rik\"  \"Olig2\"         \n",
       " [57] \"Olig1\"          \"Ifnar2\"         \"Il10rb\"         \"Ifnar1\"        \n",
       " [61] \"Ifngr2\"         \"Tmem50b\"        \"Dnajc28\"        \"Gart\"          \n",
       " [65] \"Son\"            \"Donson\"         \"Atp5o\"          \"Cryzl1\"        \n",
       " [69] \"Itsn1\"          \"Mrps6\"          \"Slc5a3\"         \"Kcne2\"         \n",
       " [73] \"4930563D23Rik\"  \"Kcne1\"          \"Rcan1\"          \"Clic6\"         \n",
       " [77] \"Runx1\"          \"mmu-miR-802\"    \"Setd4\"          \"Cbr1\"          \n",
       " [81] \"Cbr3\"           \"Dopey2\"         \"Morc3\"          \"Chaf1b\"        \n",
       " [85] \"Cldn14\"         \"Sim2\"           \"Hlcs\"           \"Ripply3\"       \n",
       " [89] \"Pigp\"           \"Ttc3\"           \"Dscr3\"          \"Dyrk1a\"        \n",
       " [93] \"Kcnj6\"          \"Kcnj15\"         \"Erg\"            \"Ets2\"          \n",
       " [97] \"Psmg1\"          \"Brwd1\"          \"Hmgn1\"          \"Wrb\"           \n",
       "[101] \"Lca5l\"          \"Sh3bgr\"         \"B3galt5\"        \"Igsf5\"         \n",
       "[105] \"Itgb2l\"         \"Dscam\"          \"Bace2\"          \"Fam3b\"         \n",
       "[109] \"Mx2\"            \"Tmprss2\"        \"Ripk4\"          \"Prdm15\"        \n",
       "[113] \"5830404H04Rik\"  \"Zfp295\"        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fig 2b - heatmap\n",
    "# for the heatmap (x-axis = broad CT; y-axis = Tri16 genes)\n",
    "# foldchange heatmap; for significance use \"*\" for padj\n",
    "# apply a % avg exp cutoff (N%)\n",
    "tri16Genes <- read.table(\"/tscc/projects/ps-epigen/users/kdang/ASAP/ifiles/trisomicGenes.txt\")$V1\n",
    "tri16Genes\n",
    "\n",
    "# deseq path\n",
    "#DE_PATH <- \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/DESeq_OUT/DESeq_byBroadCTs/DESeq_out/\"\n",
    "DE_PATH <- \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/DESeq_OUT/DESeq_byBroadCTs/DESeq_out_withNA/\"\n",
    "\n",
    "HMAP_ODIR <- \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/\"\n",
    "# before you start looping check if i can add the signif \"*\" - update i couldnt figure it out so im just gonna do it manually"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37dda2b2-aee7-4253-af28-1af2440304fb",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "### testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "28be3339-3b35-4aaa-ba4d-c412fd4d125b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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x51c3Mr9ZCcnFxkZKSamlodhwQAYsN23hHbgg/dnPpbpDbosnnv83FelvmF0QaT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OH8G732k4e9pI1Bw/bfdEq9/vdF52OHqc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J1N2aL12LEou2xGyGr26/F/ZBbM2bBy3N4U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XGPqtWlS1pB4dY+kekmu/Pe7AyB9KpdpzqPUQ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\nkaW0tDSGIgEAwNf9Pw+0TZ3rVhsrAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 720,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.height = 12, repr.plot.width = 7)\n",
    "f1 <- colorRamp2(seq(min(plotMtx), max(plotMtx), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "ht <- Heatmap(as.matrix(plotMtx), name=\"log2FoldChange\", column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", pairwise),\n",
    "              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx),\n",
    "              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx)*unit(10, \"mm\"))\n",
    "ht <- draw(ht)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "50d570b1-93f7-4b64-9700-82186fc08930",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Rbm11</th><td> 0.9048050</td><td>1.24378736</td><td>0.0000000</td><td> 0.4415870</td><td>0.7653082</td><td>0.0000000</td><td>0.0000000</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>-0.0354950</td><td>0.26766886</td><td>0.0000000</td><td>-0.1321392</td><td>0.6330854</td><td>0.1238973</td><td>0.0000000</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td> 0.6270267</td><td>0.50906155</td><td>0.2739173</td><td> 0.6349486</td><td>0.7153220</td><td>0.6186786</td><td>0.6714049</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td> 0.8312173</td><td>0.28189889</td><td>0.2195635</td><td> 1.2211080</td><td>0.6307620</td><td>0.5502641</td><td>0.0000000</td></tr>\n",
       "\t<tr><th scope=row>Cxadr</th><td> 0.9183107</td><td>0.76082137</td><td>0.9617281</td><td> 0.5807306</td><td>2.0112661</td><td>0.9926490</td><td>0.0000000</td></tr>\n",
       "\t<tr><th scope=row>Btg3</th><td> 0.6778040</td><td>0.08080128</td><td>0.0000000</td><td> 0.8150632</td><td>0.6471471</td><td>0.0000000</td><td>0.0000000</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tRbm11 &  0.9048050 & 1.24378736 & 0.0000000 &  0.4415870 & 0.7653082 & 0.0000000 & 0.0000000\\\\\n",
       "\tHspa13 & -0.0354950 & 0.26766886 & 0.0000000 & -0.1321392 & 0.6330854 & 0.1238973 & 0.0000000\\\\\n",
       "\tNrip1 &  0.6270267 & 0.50906155 & 0.2739173 &  0.6349486 & 0.7153220 & 0.6186786 & 0.6714049\\\\\n",
       "\tUsp25 &  0.8312173 & 0.28189889 & 0.2195635 &  1.2211080 & 0.6307620 & 0.5502641 & 0.0000000\\\\\n",
       "\tCxadr &  0.9183107 & 0.76082137 & 0.9617281 &  0.5807306 & 2.0112661 & 0.9926490 & 0.0000000\\\\\n",
       "\tBtg3 &  0.6778040 & 0.08080128 & 0.0000000 &  0.8150632 & 0.6471471 & 0.0000000 & 0.0000000\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 7\n",
       "\n",
       "| <!--/--> | GABAergic &lt;dbl&gt; | Glutamatergic &lt;dbl&gt; | BFCN &lt;dbl&gt; | OPC &lt;dbl&gt; | Oligodendrocyte &lt;dbl&gt; | Astrocyte &lt;dbl&gt; | Microglia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| Rbm11 |  0.9048050 | 1.24378736 | 0.0000000 |  0.4415870 | 0.7653082 | 0.0000000 | 0.0000000 |\n",
       "| Hspa13 | -0.0354950 | 0.26766886 | 0.0000000 | -0.1321392 | 0.6330854 | 0.1238973 | 0.0000000 |\n",
       "| Nrip1 |  0.6270267 | 0.50906155 | 0.2739173 |  0.6349486 | 0.7153220 | 0.6186786 | 0.6714049 |\n",
       "| Usp25 |  0.8312173 | 0.28189889 | 0.2195635 |  1.2211080 | 0.6307620 | 0.5502641 | 0.0000000 |\n",
       "| Cxadr |  0.9183107 | 0.76082137 | 0.9617281 |  0.5807306 | 2.0112661 | 0.9926490 | 0.0000000 |\n",
       "| Btg3 |  0.6778040 | 0.08080128 | 0.0000000 |  0.8150632 | 0.6471471 | 0.0000000 | 0.0000000 |\n",
       "\n"
      ],
      "text/plain": [
       "       GABAergic  Glutamatergic BFCN      OPC        Oligodendrocyte Astrocyte\n",
       "Rbm11   0.9048050 1.24378736    0.0000000  0.4415870 0.7653082       0.0000000\n",
       "Hspa13 -0.0354950 0.26766886    0.0000000 -0.1321392 0.6330854       0.1238973\n",
       "Nrip1   0.6270267 0.50906155    0.2739173  0.6349486 0.7153220       0.6186786\n",
       "Usp25   0.8312173 0.28189889    0.2195635  1.2211080 0.6307620       0.5502641\n",
       "Cxadr   0.9183107 0.76082137    0.9617281  0.5807306 2.0112661       0.9926490\n",
       "Btg3    0.6778040 0.08080128    0.0000000  0.8150632 0.6471471       0.0000000\n",
       "       Microglia\n",
       "Rbm11  0.0000000\n",
       "Hspa13 0.0000000\n",
       "Nrip1  0.6714049\n",
       "Usp25  0.0000000\n",
       "Cxadr  0.0000000\n",
       "Btg3   0.0000000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Rbm11</th><td> 0.27237343</td><td>0.37441730</td><td>0.00000000</td><td> 0.13293094</td><td>0.2303807</td><td>0.0000000</td><td>0.000000</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>-0.01068506</td><td>0.08057636</td><td>0.00000000</td><td>-0.03977785</td><td>0.1905777</td><td>0.0372968</td><td>0.000000</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td> 0.18875383</td><td>0.15324280</td><td>0.08245734</td><td> 0.19113857</td><td>0.2153334</td><td>0.1862408</td><td>0.202113</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td> 0.25022135</td><td>0.08486002</td><td>0.06609519</td><td> 0.36759012</td><td>0.1898783</td><td>0.1656460</td><td>0.000000</td></tr>\n",
       "\t<tr><th scope=row>Cxadr</th><td> 0.27643906</td><td>0.22903005</td><td>0.28950900</td><td> 0.17481732</td><td>0.6054514</td><td>0.2988171</td><td>0.000000</td></tr>\n",
       "\t<tr><th scope=row>Btg3</th><td> 0.20403934</td><td>0.02432361</td><td>0.00000000</td><td> 0.24535846</td><td>0.1948107</td><td>0.0000000</td><td>0.000000</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tRbm11 &  0.27237343 & 0.37441730 & 0.00000000 &  0.13293094 & 0.2303807 & 0.0000000 & 0.000000\\\\\n",
       "\tHspa13 & -0.01068506 & 0.08057636 & 0.00000000 & -0.03977785 & 0.1905777 & 0.0372968 & 0.000000\\\\\n",
       "\tNrip1 &  0.18875383 & 0.15324280 & 0.08245734 &  0.19113857 & 0.2153334 & 0.1862408 & 0.202113\\\\\n",
       "\tUsp25 &  0.25022135 & 0.08486002 & 0.06609519 &  0.36759012 & 0.1898783 & 0.1656460 & 0.000000\\\\\n",
       "\tCxadr &  0.27643906 & 0.22903005 & 0.28950900 &  0.17481732 & 0.6054514 & 0.2988171 & 0.000000\\\\\n",
       "\tBtg3 &  0.20403934 & 0.02432361 & 0.00000000 &  0.24535846 & 0.1948107 & 0.0000000 & 0.000000\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 7\n",
       "\n",
       "| <!--/--> | GABAergic &lt;dbl&gt; | Glutamatergic &lt;dbl&gt; | BFCN &lt;dbl&gt; | OPC &lt;dbl&gt; | Oligodendrocyte &lt;dbl&gt; | Astrocyte &lt;dbl&gt; | Microglia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| Rbm11 |  0.27237343 | 0.37441730 | 0.00000000 |  0.13293094 | 0.2303807 | 0.0000000 | 0.000000 |\n",
       "| Hspa13 | -0.01068506 | 0.08057636 | 0.00000000 | -0.03977785 | 0.1905777 | 0.0372968 | 0.000000 |\n",
       "| Nrip1 |  0.18875383 | 0.15324280 | 0.08245734 |  0.19113857 | 0.2153334 | 0.1862408 | 0.202113 |\n",
       "| Usp25 |  0.25022135 | 0.08486002 | 0.06609519 |  0.36759012 | 0.1898783 | 0.1656460 | 0.000000 |\n",
       "| Cxadr |  0.27643906 | 0.22903005 | 0.28950900 |  0.17481732 | 0.6054514 | 0.2988171 | 0.000000 |\n",
       "| Btg3 |  0.20403934 | 0.02432361 | 0.00000000 |  0.24535846 | 0.1948107 | 0.0000000 | 0.000000 |\n",
       "\n"
      ],
      "text/plain": [
       "       GABAergic   Glutamatergic BFCN       OPC         Oligodendrocyte\n",
       "Rbm11   0.27237343 0.37441730    0.00000000  0.13293094 0.2303807      \n",
       "Hspa13 -0.01068506 0.08057636    0.00000000 -0.03977785 0.1905777      \n",
       "Nrip1   0.18875383 0.15324280    0.08245734  0.19113857 0.2153334      \n",
       "Usp25   0.25022135 0.08486002    0.06609519  0.36759012 0.1898783      \n",
       "Cxadr   0.27643906 0.22903005    0.28950900  0.17481732 0.6054514      \n",
       "Btg3    0.20403934 0.02432361    0.00000000  0.24535846 0.1948107      \n",
       "       Astrocyte Microglia\n",
       "Rbm11  0.0000000 0.000000 \n",
       "Hspa13 0.0372968 0.000000 \n",
       "Nrip1  0.1862408 0.202113 \n",
       "Usp25  0.1656460 0.000000 \n",
       "Cxadr  0.2988171 0.000000 \n",
       "Btg3   0.0000000 0.000000 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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goSO/YpKCikpaWVeWrbtm0+Pj51HA8A1CeOMw84Fh50dutjmdrQfv3OJz6LrAoK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8XQMA4JTutraK9PfBmL+/4tpdOZFefhNN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V6k/i9rBQUFrqPveXkV0E1FhbuGSv1DAACQ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zQsnFxcump/vcDPyysgRUVFxsNBQ8wnTesmlbRr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\nnK2teVN9LGxtZCk5OZmhSAAA8M/8H4ReSEkvHeyXAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 720,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# above heatmap is smooshing the other vals with the super high log2FC's; try log10(FC)?\n",
    "head(plotMtx)\n",
    "\n",
    "plotMtx_log10 <- plotMtx / log2(10)\n",
    "head(plotMtx_log10)\n",
    "\n",
    "# TODO: CHANGE THIS TO 0 = WHITE\n",
    "f1 <- colorRamp2(seq(min(plotMtx_log10), max(plotMtx_log10), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "ht <- Heatmap(as.matrix(plotMtx_log10), name=\"log10FoldChange\", column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", pairwise),\n",
    "              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx_log10),\n",
    "              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx_log10)*unit(10, \"mm\"))\n",
    "ht <- draw(ht)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "089d4fcc-511c-4169-9e4a-c18f9a1c05a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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eHbLz9/9ypoTCOuwfJjz83s0tUt0nLf7cvLOinylsGniHdyVpNX7jx6LuT47oW9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KTUoqIaPqCzF26gkvM6ftny23XzrkoS1c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\n1X0Gnta0Gr171wTsew4A/y8UdgAAXOK8Nzef7QwA8MPCHDsAAACAOgI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9fv2aGjRowHA6AIDahMKOC+TdV/3ePW2j5/SgF1X/KarXYTgi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\nRIYiAQAAV/wPvOD0rZNd/IYAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 720,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# try zscore\n",
    "plotMtx_zsc <- t(scale(t(plotMtx)))\n",
    "\n",
    "f1 <- colorRamp2(seq(min(plotMtx_zsc), max(plotMtx_zsc), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "ht <- Heatmap(as.matrix(plotMtx_zsc), name=\"Z-score log2FoldChange\", column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", pairwise),\n",
    "              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx_zsc),\n",
    "              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx_zsc)*unit(10, \"mm\"))\n",
    "ht <- draw(ht)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15f49618-a714-42e2-82f0-b8ac30932766",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "### right now it's just different ways of plotting logFC's apply the pct exp cutoff N% (@ least 1 broadCT must exp gene by N%)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c4c2351c-6643-4ec1-a30e-34aadfe52b4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "DefaultAssay(sobj) <- \"RNA\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e3a5d62d-b14e-470a-905b-8bea55793a44",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“\u001b[1m\u001b[22mThe following features were omitted as they were not found:\n",
      "\u001b[36mℹ\u001b[39m \u001b[32mmmu-miR-99a, mmu-let-7c-1, mmu-miR-125b-2, Prss7, mmu-miR-155, Zfp294, Orf63,\u001b[39m\n",
      "  \u001b[32mGm312, Krtap16, Krtap16-7, Krtap16-4, Krtap8-2, Sfrs15, 2610039C10Rik,\u001b[39m\n",
      "  \u001b[32m4931408A02Rik, 1110004E09Rik, 1810007M14Rik, 4930563D23Rik, mmu-miR-802,\u001b[39m\n",
      "  \u001b[32mDopey2, Dscr3, Mx2, 5830404H04Rik, and Zfp295\u001b[39m”\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 90 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Doublet</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Lipi</th><td> 0.045051810</td><td> 0.13425822</td><td> 0.15625</td><td> 0.0000000</td><td> 0.07818608</td><td> 0.00000000</td><td> 0.03838772</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Rbm11</th><td> 5.684870935</td><td> 6.31013650</td><td>19.06250</td><td> 7.3637703</td><td> 5.08209539</td><td> 1.06962664</td><td> 1.84261036</td><td> 0.12714558</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>13.639018204</td><td>16.17811591</td><td>22.34375</td><td>12.6165930</td><td>10.71149335</td><td> 1.68516650</td><td> 8.00383877</td><td> 1.52574698</td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td> 0.320368424</td><td> 0.71604386</td><td> 1.25000</td><td> 0.3436426</td><td> 6.33307271</td><td> 0.02018163</td><td> 0.32629559</td><td>11.34774317</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td>23.236722231</td><td>27.38867756</td><td>62.81250</td><td>21.8949435</td><td>34.40187647</td><td> 9.67709384</td><td>18.11900192</td><td>39.06547997</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td>29.585690210</td><td>38.28597002</td><td>50.46875</td><td>24.5949926</td><td>26.58326818</td><td>15.46922301</td><td>19.25143954</td><td>11.79275270</td></tr>\n",
       "\t<tr><th scope=row>Cxadr</th><td>26.480452520</td><td>32.13246811</td><td>36.40625</td><td>18.9494354</td><td>19.07740422</td><td> 0.40363269</td><td> 8.36852207</td><td> 0.63572791</td></tr>\n",
       "\t<tr><th scope=row>Btg3</th><td>11.720144833</td><td>12.27343925</td><td>12.96875</td><td> 7.8055965</td><td> 7.97498045</td><td> 0.51463169</td><td> 4.60652591</td><td> 1.23966942</td></tr>\n",
       "\t<tr><th scope=row>D16Ertd472e</th><td> 2.491198211</td><td> 4.02774670</td><td> 1.71875</td><td> 4.4182622</td><td> 5.47302580</td><td>13.62260343</td><td> 2.47600768</td><td> 0.60394151</td></tr>\n",
       "\t<tr><th scope=row>Chodl</th><td> 1.957250838</td><td> 1.29782949</td><td> 0.46875</td><td> 0.9327442</td><td> 0.93823299</td><td> 0.05045409</td><td> 0.63339731</td><td> 0.03178640</td></tr>\n",
       "\t<tr><th scope=row>Ncam2</th><td>70.671271963</td><td>85.19803088</td><td>77.65625</td><td>94.4526264</td><td>62.00156372</td><td>63.84460141</td><td>51.22840691</td><td> 2.19326128</td></tr>\n",
       "\t<tr><th scope=row>Mrpl39</th><td> 6.912949892</td><td> 8.50302081</td><td> 9.68750</td><td> 5.6455572</td><td> 5.16028147</td><td> 1.87689203</td><td> 4.06909789</td><td> 1.65289256</td></tr>\n",
       "\t<tr><th scope=row>Jam2</th><td> 3.670888188</td><td> 5.28082345</td><td> 3.59375</td><td>25.4295533</td><td> 6.88037529</td><td> 0.87790111</td><td>16.25719770</td><td> 5.84869676</td></tr>\n",
       "\t<tr><th scope=row>Atp5j</th><td>26.947656472</td><td>30.49899306</td><td>36.25000</td><td>21.6003927</td><td>20.56293980</td><td> 5.43895055</td><td>19.04030710</td><td> 4.41830896</td></tr>\n",
       "\t<tr><th scope=row>Gabpa</th><td>12.921526422</td><td>15.05929738</td><td>17.18750</td><td>11.5856652</td><td>10.63330727</td><td> 3.38042381</td><td> 7.86948177</td><td> 2.98792117</td></tr>\n",
       "\t<tr><th scope=row>App</th><td>91.929051743</td><td>94.55135377</td><td>97.50000</td><td>68.5321551</td><td>78.81157154</td><td>75.43895055</td><td>35.27831094</td><td> 9.47234584</td></tr>\n",
       "\t<tr><th scope=row>Cyyr1</th><td> 0.545627472</td><td> 1.76773327</td><td> 9.53125</td><td> 0.3436426</td><td> 0.93823299</td><td> 0.07063572</td><td> 0.13435701</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Adamts1</th><td> 0.892693264</td><td> 2.31595435</td><td> 0.78125</td><td> 5.1055474</td><td> 2.42376857</td><td> 3.88496468</td><td> 1.43953935</td><td> 0.34965035</td></tr>\n",
       "\t<tr><th scope=row>Adamts5</th><td> 1.159666950</td><td> 1.23070038</td><td> 0.62500</td><td> 6.2346588</td><td> 0.86004691</td><td> 0.08072654</td><td> 0.42226488</td><td> 0.06357279</td></tr>\n",
       "\t<tr><th scope=row>N6amt1</th><td> 9.250638234</td><td>10.41620049</td><td>10.62500</td><td> 7.2655866</td><td> 4.76935106</td><td> 0.72653885</td><td> 4.22264875</td><td> 1.08073744</td></tr>\n",
       "\t<tr><th scope=row>Rwdd2b</th><td> 1.716974521</td><td> 2.10337883</td><td> 2.03125</td><td> 1.7182131</td><td> 1.25097733</td><td> 0.34308779</td><td> 1.03646833</td><td> 0.19071837</td></tr>\n",
       "\t<tr><th scope=row>Usp16</th><td>31.614690227</td><td>38.21884090</td><td>42.50000</td><td>31.5660285</td><td>23.76856919</td><td> 8.68819374</td><td>16.08445298</td><td> 5.88048315</td></tr>\n",
       "\t<tr><th scope=row>Cct8</th><td>18.317732059</td><td>22.53300515</td><td>27.65625</td><td>14.7275405</td><td>13.60437842</td><td> 3.01715439</td><td> 9.23224568</td><td> 2.63827082</td></tr>\n",
       "\t<tr><th scope=row>Bach1</th><td> 7.962490197</td><td>10.36025957</td><td>19.84375</td><td> 8.0510555</td><td> 9.61688819</td><td> 2.69424823</td><td> 4.93282150</td><td> 8.23267641</td></tr>\n",
       "\t<tr><th scope=row>Grik1</th><td>40.539954281</td><td>42.85074961</td><td>40.00000</td><td>52.5773196</td><td>34.48006255</td><td> 9.79818365</td><td>11.74664107</td><td> 1.36681500</td></tr>\n",
       "\t<tr><th scope=row>Cldn17</th><td> 0.001668586</td><td> 0.00000000</td><td> 0.00000</td><td> 0.0000000</td><td> 0.00000000</td><td> 0.03027245</td><td> 0.00000000</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Cldn8</th><td> 0.008342928</td><td> 0.02237637</td><td> 0.00000</td><td> 0.0000000</td><td> 0.00000000</td><td> 0.04036327</td><td> 0.01919386</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Krtap26-1</th><td> 0.000000000</td><td> 0.00000000</td><td> 0.15625</td><td> 0.0000000</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Krtap13-1</th><td> 0.000000000</td><td> 0.00000000</td><td> 0.00000</td><td> 0.0000000</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Krtap13</th><td> 0.000000000</td><td> 0.00000000</td><td> 0.00000</td><td> 0.0000000</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>Cbr1</th><td>15.25754618</td><td>18.06891922</td><td>29.53125</td><td>12.6165930</td><td>11.10242377</td><td> 2.09889001</td><td> 8.56046065</td><td> 1.65289256</td></tr>\n",
       "\t<tr><th scope=row>Cbr3</th><td> 5.11254609</td><td> 1.82367420</td><td> 5.00000</td><td> 7.7565047</td><td> 3.90930414</td><td> 0.06054490</td><td> 6.14203455</td><td> 0.66751430</td></tr>\n",
       "\t<tr><th scope=row>Morc3</th><td>23.09989822</td><td>28.41799060</td><td>39.84375</td><td>20.1767305</td><td>23.92494136</td><td> 4.48032291</td><td>14.45297505</td><td>18.05467260</td></tr>\n",
       "\t<tr><th scope=row>Chaf1b</th><td> 0.10845806</td><td> 0.12307004</td><td> 0.31250</td><td> 0.0490918</td><td> 0.23455825</td><td> 0.11099899</td><td> 0.05758157</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Cldn14</th><td> 0.31202550</td><td> 0.34683374</td><td> 0.46875</td><td> 1.0309278</td><td> 1.17279124</td><td> 4.52068618</td><td> 0.46065259</td><td> 0.06357279</td></tr>\n",
       "\t<tr><th scope=row>Sim2</th><td> 0.49890708</td><td> 0.55940926</td><td> 0.31250</td><td> 0.1963672</td><td> 0.23455825</td><td> 0.00000000</td><td> 0.11516315</td><td> 0.09535919</td></tr>\n",
       "\t<tr><th scope=row>Hlcs</th><td>37.80013682</td><td>41.86618930</td><td>48.75000</td><td>29.4550810</td><td>29.16340891</td><td> 6.04439960</td><td>22.05374280</td><td> 5.05403687</td></tr>\n",
       "\t<tr><th scope=row>Ripply3</th><td> 0.05840049</td><td> 0.12307004</td><td> 0.00000</td><td> 0.0490918</td><td> 0.07818608</td><td> 0.01009082</td><td> 0.03838772</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Pigp</th><td>22.52590479</td><td>24.97202954</td><td>37.81250</td><td>18.6548846</td><td>19.15559030</td><td> 4.94450050</td><td>16.14203455</td><td> 2.47933884</td></tr>\n",
       "\t<tr><th scope=row>Ttc3</th><td>96.26737415</td><td>97.66166928</td><td>98.59375</td><td>72.2140403</td><td>76.15324472</td><td>11.85671039</td><td>39.55854127</td><td> 8.32803560</td></tr>\n",
       "\t<tr><th scope=row>Dyrk1a</th><td>56.78363451</td><td>65.80890580</td><td>70.78125</td><td>46.1953854</td><td>45.73885848</td><td>16.97275479</td><td>33.93474088</td><td>19.80292435</td></tr>\n",
       "\t<tr><th scope=row>Kcnj6</th><td>35.84288599</td><td>59.38688745</td><td>28.12500</td><td>16.8875798</td><td>24.78498827</td><td> 0.50454087</td><td> 7.83109405</td><td> 1.11252384</td></tr>\n",
       "\t<tr><th scope=row>Kcnj15</th><td> 0.01501727</td><td> 0.11188185</td><td> 0.00000</td><td> 0.0000000</td><td> 0.00000000</td><td> 0.01009082</td><td> 0.00000000</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Erg</th><td> 0.28199096</td><td> 0.25732826</td><td> 0.46875</td><td> 0.1963672</td><td> 0.23455825</td><td> 0.03027245</td><td> 0.17274472</td><td> 0.03178640</td></tr>\n",
       "\t<tr><th scope=row>Ets2</th><td>20.94074853</td><td>21.50369210</td><td>10.93750</td><td>12.0765832</td><td>13.05707584</td><td> 0.26236125</td><td> 7.21689060</td><td> 0.85823268</td></tr>\n",
       "\t<tr><th scope=row>Psmg1</th><td> 5.42790876</td><td> 6.42201835</td><td> 5.46875</td><td> 4.4673540</td><td> 4.61297889</td><td> 0.92835520</td><td> 2.72552783</td><td> 0.89001907</td></tr>\n",
       "\t<tr><th scope=row>Brwd1</th><td>64.74445612</td><td>71.52606847</td><td>78.28125</td><td>48.7972509</td><td>50.97732604</td><td>18.62764884</td><td>33.22456814</td><td>13.57279085</td></tr>\n",
       "\t<tr><th scope=row>Hmgn1</th><td>21.11595001</td><td>22.26448870</td><td>25.46875</td><td>15.8075601</td><td>15.08991400</td><td> 2.57315843</td><td>10.38387716</td><td> 3.33757152</td></tr>\n",
       "\t<tr><th scope=row>Wrb</th><td>15.00392118</td><td>18.12486015</td><td>19.84375</td><td>10.0638193</td><td>10.63330727</td><td> 1.26135217</td><td> 5.96928983</td><td> 1.49396058</td></tr>\n",
       "\t<tr><th scope=row>Lca5l</th><td>14.78533647</td><td>18.16961289</td><td>20.46875</td><td>10.2110947</td><td> 9.92963253</td><td> 0.49445005</td><td> 4.97120921</td><td> 2.22504768</td></tr>\n",
       "\t<tr><th scope=row>Sh3bgr</th><td> 0.74418915</td><td> 0.87267845</td><td> 2.03125</td><td> 0.4909180</td><td> 0.15637217</td><td> 0.02018163</td><td> 0.23032630</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>B3galt5</th><td>25.05381188</td><td>21.21279928</td><td>22.18750</td><td>14.2857143</td><td>21.81391712</td><td>22.10898083</td><td>10.07677543</td><td> 5.94405594</td></tr>\n",
       "\t<tr><th scope=row>Igsf5</th><td> 0.24027632</td><td> 0.19019915</td><td> 2.50000</td><td> 0.1963672</td><td> 0.07818608</td><td> 0.30272452</td><td> 0.17274472</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Itgb2l</th><td> 0.01668586</td><td> 0.02237637</td><td> 0.31250</td><td> 0.0000000</td><td> 0.00000000</td><td> 0.01009082</td><td> 0.01919386</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Dscam</th><td>67.47259348</td><td>92.15708212</td><td>99.37500</td><td>97.7417771</td><td>44.17513683</td><td> 4.26841574</td><td>16.08445298</td><td> 2.32040687</td></tr>\n",
       "\t<tr><th scope=row>Bace2</th><td> 1.22807896</td><td> 1.98030879</td><td> 0.62500</td><td> 0.5891016</td><td> 0.86004691</td><td> 0.34308779</td><td> 0.51823417</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Fam3b</th><td> 0.16518997</td><td> 0.16782278</td><td> 0.00000</td><td> 0.0981836</td><td> 0.15637217</td><td> 0.01009082</td><td> 0.01919386</td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Tmprss2</th><td> 0.05005757</td><td> 0.04475274</td><td> 0.15625</td><td> 0.0000000</td><td> 0.07818608</td><td> 0.04036327</td><td> 0.05758157</td><td> 0.03178640</td></tr>\n",
       "\t<tr><th scope=row>Ripk4</th><td> 1.07123192</td><td> 0.92861938</td><td> 2.34375</td><td> 0.4909180</td><td> 0.62548866</td><td> 0.29263370</td><td> 0.74856046</td><td> 0.03178640</td></tr>\n",
       "\t<tr><th scope=row>Prdm15</th><td>21.29949442</td><td>26.51599910</td><td>30.78125</td><td>14.7275405</td><td>13.68256450</td><td> 2.13925328</td><td> 8.69481766</td><td> 3.59186268</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 90 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Doublet & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tLipi &  0.045051810 &  0.13425822 &  0.15625 &  0.0000000 &  0.07818608 &  0.00000000 &  0.03838772 &  0.00000000\\\\\n",
       "\tRbm11 &  5.684870935 &  6.31013650 & 19.06250 &  7.3637703 &  5.08209539 &  1.06962664 &  1.84261036 &  0.12714558\\\\\n",
       "\tHspa13 & 13.639018204 & 16.17811591 & 22.34375 & 12.6165930 & 10.71149335 &  1.68516650 &  8.00383877 &  1.52574698\\\\\n",
       "\tSamsn1 &  0.320368424 &  0.71604386 &  1.25000 &  0.3436426 &  6.33307271 &  0.02018163 &  0.32629559 & 11.34774317\\\\\n",
       "\tNrip1 & 23.236722231 & 27.38867756 & 62.81250 & 21.8949435 & 34.40187647 &  9.67709384 & 18.11900192 & 39.06547997\\\\\n",
       "\tUsp25 & 29.585690210 & 38.28597002 & 50.46875 & 24.5949926 & 26.58326818 & 15.46922301 & 19.25143954 & 11.79275270\\\\\n",
       "\tCxadr & 26.480452520 & 32.13246811 & 36.40625 & 18.9494354 & 19.07740422 &  0.40363269 &  8.36852207 &  0.63572791\\\\\n",
       "\tBtg3 & 11.720144833 & 12.27343925 & 12.96875 &  7.8055965 &  7.97498045 &  0.51463169 &  4.60652591 &  1.23966942\\\\\n",
       "\tD16Ertd472e &  2.491198211 &  4.02774670 &  1.71875 &  4.4182622 &  5.47302580 & 13.62260343 &  2.47600768 &  0.60394151\\\\\n",
       "\tChodl &  1.957250838 &  1.29782949 &  0.46875 &  0.9327442 &  0.93823299 &  0.05045409 &  0.63339731 &  0.03178640\\\\\n",
       "\tNcam2 & 70.671271963 & 85.19803088 & 77.65625 & 94.4526264 & 62.00156372 & 63.84460141 & 51.22840691 &  2.19326128\\\\\n",
       "\tMrpl39 &  6.912949892 &  8.50302081 &  9.68750 &  5.6455572 &  5.16028147 &  1.87689203 &  4.06909789 &  1.65289256\\\\\n",
       "\tJam2 &  3.670888188 &  5.28082345 &  3.59375 & 25.4295533 &  6.88037529 &  0.87790111 & 16.25719770 &  5.84869676\\\\\n",
       "\tAtp5j & 26.947656472 & 30.49899306 & 36.25000 & 21.6003927 & 20.56293980 &  5.43895055 & 19.04030710 &  4.41830896\\\\\n",
       "\tGabpa & 12.921526422 & 15.05929738 & 17.18750 & 11.5856652 & 10.63330727 &  3.38042381 &  7.86948177 &  2.98792117\\\\\n",
       "\tApp & 91.929051743 & 94.55135377 & 97.50000 & 68.5321551 & 78.81157154 & 75.43895055 & 35.27831094 &  9.47234584\\\\\n",
       "\tCyyr1 &  0.545627472 &  1.76773327 &  9.53125 &  0.3436426 &  0.93823299 &  0.07063572 &  0.13435701 &  0.00000000\\\\\n",
       "\tAdamts1 &  0.892693264 &  2.31595435 &  0.78125 &  5.1055474 &  2.42376857 &  3.88496468 &  1.43953935 &  0.34965035\\\\\n",
       "\tAdamts5 &  1.159666950 &  1.23070038 &  0.62500 &  6.2346588 &  0.86004691 &  0.08072654 &  0.42226488 &  0.06357279\\\\\n",
       "\tN6amt1 &  9.250638234 & 10.41620049 & 10.62500 &  7.2655866 &  4.76935106 &  0.72653885 &  4.22264875 &  1.08073744\\\\\n",
       "\tRwdd2b &  1.716974521 &  2.10337883 &  2.03125 &  1.7182131 &  1.25097733 &  0.34308779 &  1.03646833 &  0.19071837\\\\\n",
       "\tUsp16 & 31.614690227 & 38.21884090 & 42.50000 & 31.5660285 & 23.76856919 &  8.68819374 & 16.08445298 &  5.88048315\\\\\n",
       "\tCct8 & 18.317732059 & 22.53300515 & 27.65625 & 14.7275405 & 13.60437842 &  3.01715439 &  9.23224568 &  2.63827082\\\\\n",
       "\tBach1 &  7.962490197 & 10.36025957 & 19.84375 &  8.0510555 &  9.61688819 &  2.69424823 &  4.93282150 &  8.23267641\\\\\n",
       "\tGrik1 & 40.539954281 & 42.85074961 & 40.00000 & 52.5773196 & 34.48006255 &  9.79818365 & 11.74664107 &  1.36681500\\\\\n",
       "\tCldn17 &  0.001668586 &  0.00000000 &  0.00000 &  0.0000000 &  0.00000000 &  0.03027245 &  0.00000000 &  0.00000000\\\\\n",
       "\tCldn8 &  0.008342928 &  0.02237637 &  0.00000 &  0.0000000 &  0.00000000 &  0.04036327 &  0.01919386 &  0.00000000\\\\\n",
       "\tKrtap26-1 &  0.000000000 &  0.00000000 &  0.15625 &  0.0000000 &  0.00000000 &  0.00000000 &  0.00000000 &  0.00000000\\\\\n",
       "\tKrtap13-1 &  0.000000000 &  0.00000000 &  0.00000 &  0.0000000 &  0.00000000 &  0.00000000 &  0.00000000 &  0.00000000\\\\\n",
       "\tKrtap13 &  0.000000000 &  0.00000000 &  0.00000 &  0.0000000 &  0.00000000 &  0.00000000 &  0.00000000 &  0.00000000\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\tCbr1 & 15.25754618 & 18.06891922 & 29.53125 & 12.6165930 & 11.10242377 &  2.09889001 &  8.56046065 &  1.65289256\\\\\n",
       "\tCbr3 &  5.11254609 &  1.82367420 &  5.00000 &  7.7565047 &  3.90930414 &  0.06054490 &  6.14203455 &  0.66751430\\\\\n",
       "\tMorc3 & 23.09989822 & 28.41799060 & 39.84375 & 20.1767305 & 23.92494136 &  4.48032291 & 14.45297505 & 18.05467260\\\\\n",
       "\tChaf1b &  0.10845806 &  0.12307004 &  0.31250 &  0.0490918 &  0.23455825 &  0.11099899 &  0.05758157 &  0.00000000\\\\\n",
       "\tCldn14 &  0.31202550 &  0.34683374 &  0.46875 &  1.0309278 &  1.17279124 &  4.52068618 &  0.46065259 &  0.06357279\\\\\n",
       "\tSim2 &  0.49890708 &  0.55940926 &  0.31250 &  0.1963672 &  0.23455825 &  0.00000000 &  0.11516315 &  0.09535919\\\\\n",
       "\tHlcs & 37.80013682 & 41.86618930 & 48.75000 & 29.4550810 & 29.16340891 &  6.04439960 & 22.05374280 &  5.05403687\\\\\n",
       "\tRipply3 &  0.05840049 &  0.12307004 &  0.00000 &  0.0490918 &  0.07818608 &  0.01009082 &  0.03838772 &  0.00000000\\\\\n",
       "\tPigp & 22.52590479 & 24.97202954 & 37.81250 & 18.6548846 & 19.15559030 &  4.94450050 & 16.14203455 &  2.47933884\\\\\n",
       "\tTtc3 & 96.26737415 & 97.66166928 & 98.59375 & 72.2140403 & 76.15324472 & 11.85671039 & 39.55854127 &  8.32803560\\\\\n",
       "\tDyrk1a & 56.78363451 & 65.80890580 & 70.78125 & 46.1953854 & 45.73885848 & 16.97275479 & 33.93474088 & 19.80292435\\\\\n",
       "\tKcnj6 & 35.84288599 & 59.38688745 & 28.12500 & 16.8875798 & 24.78498827 &  0.50454087 &  7.83109405 &  1.11252384\\\\\n",
       "\tKcnj15 &  0.01501727 &  0.11188185 &  0.00000 &  0.0000000 &  0.00000000 &  0.01009082 &  0.00000000 &  0.00000000\\\\\n",
       "\tErg &  0.28199096 &  0.25732826 &  0.46875 &  0.1963672 &  0.23455825 &  0.03027245 &  0.17274472 &  0.03178640\\\\\n",
       "\tEts2 & 20.94074853 & 21.50369210 & 10.93750 & 12.0765832 & 13.05707584 &  0.26236125 &  7.21689060 &  0.85823268\\\\\n",
       "\tPsmg1 &  5.42790876 &  6.42201835 &  5.46875 &  4.4673540 &  4.61297889 &  0.92835520 &  2.72552783 &  0.89001907\\\\\n",
       "\tBrwd1 & 64.74445612 & 71.52606847 & 78.28125 & 48.7972509 & 50.97732604 & 18.62764884 & 33.22456814 & 13.57279085\\\\\n",
       "\tHmgn1 & 21.11595001 & 22.26448870 & 25.46875 & 15.8075601 & 15.08991400 &  2.57315843 & 10.38387716 &  3.33757152\\\\\n",
       "\tWrb & 15.00392118 & 18.12486015 & 19.84375 & 10.0638193 & 10.63330727 &  1.26135217 &  5.96928983 &  1.49396058\\\\\n",
       "\tLca5l & 14.78533647 & 18.16961289 & 20.46875 & 10.2110947 &  9.92963253 &  0.49445005 &  4.97120921 &  2.22504768\\\\\n",
       "\tSh3bgr &  0.74418915 &  0.87267845 &  2.03125 &  0.4909180 &  0.15637217 &  0.02018163 &  0.23032630 &  0.00000000\\\\\n",
       "\tB3galt5 & 25.05381188 & 21.21279928 & 22.18750 & 14.2857143 & 21.81391712 & 22.10898083 & 10.07677543 &  5.94405594\\\\\n",
       "\tIgsf5 &  0.24027632 &  0.19019915 &  2.50000 &  0.1963672 &  0.07818608 &  0.30272452 &  0.17274472 &  0.00000000\\\\\n",
       "\tItgb2l &  0.01668586 &  0.02237637 &  0.31250 &  0.0000000 &  0.00000000 &  0.01009082 &  0.01919386 &  0.00000000\\\\\n",
       "\tDscam & 67.47259348 & 92.15708212 & 99.37500 & 97.7417771 & 44.17513683 &  4.26841574 & 16.08445298 &  2.32040687\\\\\n",
       "\tBace2 &  1.22807896 &  1.98030879 &  0.62500 &  0.5891016 &  0.86004691 &  0.34308779 &  0.51823417 &  0.00000000\\\\\n",
       "\tFam3b &  0.16518997 &  0.16782278 &  0.00000 &  0.0981836 &  0.15637217 &  0.01009082 &  0.01919386 &  0.00000000\\\\\n",
       "\tTmprss2 &  0.05005757 &  0.04475274 &  0.15625 &  0.0000000 &  0.07818608 &  0.04036327 &  0.05758157 &  0.03178640\\\\\n",
       "\tRipk4 &  1.07123192 &  0.92861938 &  2.34375 &  0.4909180 &  0.62548866 &  0.29263370 &  0.74856046 &  0.03178640\\\\\n",
       "\tPrdm15 & 21.29949442 & 26.51599910 & 30.78125 & 14.7275405 & 13.68256450 &  2.13925328 &  8.69481766 &  3.59186268\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 90 × 8\n",
       "\n",
       "| <!--/--> | GABAergic &lt;dbl&gt; | Glutamatergic &lt;dbl&gt; | BFCN &lt;dbl&gt; | OPC &lt;dbl&gt; | Doublet &lt;dbl&gt; | Oligodendrocyte &lt;dbl&gt; | Astrocyte &lt;dbl&gt; | Microglia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| Lipi |  0.045051810 |  0.13425822 |  0.15625 |  0.0000000 |  0.07818608 |  0.00000000 |  0.03838772 |  0.00000000 |\n",
       "| Rbm11 |  5.684870935 |  6.31013650 | 19.06250 |  7.3637703 |  5.08209539 |  1.06962664 |  1.84261036 |  0.12714558 |\n",
       "| Hspa13 | 13.639018204 | 16.17811591 | 22.34375 | 12.6165930 | 10.71149335 |  1.68516650 |  8.00383877 |  1.52574698 |\n",
       "| Samsn1 |  0.320368424 |  0.71604386 |  1.25000 |  0.3436426 |  6.33307271 |  0.02018163 |  0.32629559 | 11.34774317 |\n",
       "| Nrip1 | 23.236722231 | 27.38867756 | 62.81250 | 21.8949435 | 34.40187647 |  9.67709384 | 18.11900192 | 39.06547997 |\n",
       "| Usp25 | 29.585690210 | 38.28597002 | 50.46875 | 24.5949926 | 26.58326818 | 15.46922301 | 19.25143954 | 11.79275270 |\n",
       "| Cxadr | 26.480452520 | 32.13246811 | 36.40625 | 18.9494354 | 19.07740422 |  0.40363269 |  8.36852207 |  0.63572791 |\n",
       "| Btg3 | 11.720144833 | 12.27343925 | 12.96875 |  7.8055965 |  7.97498045 |  0.51463169 |  4.60652591 |  1.23966942 |\n",
       "| D16Ertd472e |  2.491198211 |  4.02774670 |  1.71875 |  4.4182622 |  5.47302580 | 13.62260343 |  2.47600768 |  0.60394151 |\n",
       "| Chodl |  1.957250838 |  1.29782949 |  0.46875 |  0.9327442 |  0.93823299 |  0.05045409 |  0.63339731 |  0.03178640 |\n",
       "| Ncam2 | 70.671271963 | 85.19803088 | 77.65625 | 94.4526264 | 62.00156372 | 63.84460141 | 51.22840691 |  2.19326128 |\n",
       "| Mrpl39 |  6.912949892 |  8.50302081 |  9.68750 |  5.6455572 |  5.16028147 |  1.87689203 |  4.06909789 |  1.65289256 |\n",
       "| Jam2 |  3.670888188 |  5.28082345 |  3.59375 | 25.4295533 |  6.88037529 |  0.87790111 | 16.25719770 |  5.84869676 |\n",
       "| Atp5j | 26.947656472 | 30.49899306 | 36.25000 | 21.6003927 | 20.56293980 |  5.43895055 | 19.04030710 |  4.41830896 |\n",
       "| Gabpa | 12.921526422 | 15.05929738 | 17.18750 | 11.5856652 | 10.63330727 |  3.38042381 |  7.86948177 |  2.98792117 |\n",
       "| App | 91.929051743 | 94.55135377 | 97.50000 | 68.5321551 | 78.81157154 | 75.43895055 | 35.27831094 |  9.47234584 |\n",
       "| Cyyr1 |  0.545627472 |  1.76773327 |  9.53125 |  0.3436426 |  0.93823299 |  0.07063572 |  0.13435701 |  0.00000000 |\n",
       "| Adamts1 |  0.892693264 |  2.31595435 |  0.78125 |  5.1055474 |  2.42376857 |  3.88496468 |  1.43953935 |  0.34965035 |\n",
       "| Adamts5 |  1.159666950 |  1.23070038 |  0.62500 |  6.2346588 |  0.86004691 |  0.08072654 |  0.42226488 |  0.06357279 |\n",
       "| N6amt1 |  9.250638234 | 10.41620049 | 10.62500 |  7.2655866 |  4.76935106 |  0.72653885 |  4.22264875 |  1.08073744 |\n",
       "| Rwdd2b |  1.716974521 |  2.10337883 |  2.03125 |  1.7182131 |  1.25097733 |  0.34308779 |  1.03646833 |  0.19071837 |\n",
       "| Usp16 | 31.614690227 | 38.21884090 | 42.50000 | 31.5660285 | 23.76856919 |  8.68819374 | 16.08445298 |  5.88048315 |\n",
       "| Cct8 | 18.317732059 | 22.53300515 | 27.65625 | 14.7275405 | 13.60437842 |  3.01715439 |  9.23224568 |  2.63827082 |\n",
       "| Bach1 |  7.962490197 | 10.36025957 | 19.84375 |  8.0510555 |  9.61688819 |  2.69424823 |  4.93282150 |  8.23267641 |\n",
       "| Grik1 | 40.539954281 | 42.85074961 | 40.00000 | 52.5773196 | 34.48006255 |  9.79818365 | 11.74664107 |  1.36681500 |\n",
       "| Cldn17 |  0.001668586 |  0.00000000 |  0.00000 |  0.0000000 |  0.00000000 |  0.03027245 |  0.00000000 |  0.00000000 |\n",
       "| Cldn8 |  0.008342928 |  0.02237637 |  0.00000 |  0.0000000 |  0.00000000 |  0.04036327 |  0.01919386 |  0.00000000 |\n",
       "| Krtap26-1 |  0.000000000 |  0.00000000 |  0.15625 |  0.0000000 |  0.00000000 |  0.00000000 |  0.00000000 |  0.00000000 |\n",
       "| Krtap13-1 |  0.000000000 |  0.00000000 |  0.00000 |  0.0000000 |  0.00000000 |  0.00000000 |  0.00000000 |  0.00000000 |\n",
       "| Krtap13 |  0.000000000 |  0.00000000 |  0.00000 |  0.0000000 |  0.00000000 |  0.00000000 |  0.00000000 |  0.00000000 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| Cbr1 | 15.25754618 | 18.06891922 | 29.53125 | 12.6165930 | 11.10242377 |  2.09889001 |  8.56046065 |  1.65289256 |\n",
       "| Cbr3 |  5.11254609 |  1.82367420 |  5.00000 |  7.7565047 |  3.90930414 |  0.06054490 |  6.14203455 |  0.66751430 |\n",
       "| Morc3 | 23.09989822 | 28.41799060 | 39.84375 | 20.1767305 | 23.92494136 |  4.48032291 | 14.45297505 | 18.05467260 |\n",
       "| Chaf1b |  0.10845806 |  0.12307004 |  0.31250 |  0.0490918 |  0.23455825 |  0.11099899 |  0.05758157 |  0.00000000 |\n",
       "| Cldn14 |  0.31202550 |  0.34683374 |  0.46875 |  1.0309278 |  1.17279124 |  4.52068618 |  0.46065259 |  0.06357279 |\n",
       "| Sim2 |  0.49890708 |  0.55940926 |  0.31250 |  0.1963672 |  0.23455825 |  0.00000000 |  0.11516315 |  0.09535919 |\n",
       "| Hlcs | 37.80013682 | 41.86618930 | 48.75000 | 29.4550810 | 29.16340891 |  6.04439960 | 22.05374280 |  5.05403687 |\n",
       "| Ripply3 |  0.05840049 |  0.12307004 |  0.00000 |  0.0490918 |  0.07818608 |  0.01009082 |  0.03838772 |  0.00000000 |\n",
       "| Pigp | 22.52590479 | 24.97202954 | 37.81250 | 18.6548846 | 19.15559030 |  4.94450050 | 16.14203455 |  2.47933884 |\n",
       "| Ttc3 | 96.26737415 | 97.66166928 | 98.59375 | 72.2140403 | 76.15324472 | 11.85671039 | 39.55854127 |  8.32803560 |\n",
       "| Dyrk1a | 56.78363451 | 65.80890580 | 70.78125 | 46.1953854 | 45.73885848 | 16.97275479 | 33.93474088 | 19.80292435 |\n",
       "| Kcnj6 | 35.84288599 | 59.38688745 | 28.12500 | 16.8875798 | 24.78498827 |  0.50454087 |  7.83109405 |  1.11252384 |\n",
       "| Kcnj15 |  0.01501727 |  0.11188185 |  0.00000 |  0.0000000 |  0.00000000 |  0.01009082 |  0.00000000 |  0.00000000 |\n",
       "| Erg |  0.28199096 |  0.25732826 |  0.46875 |  0.1963672 |  0.23455825 |  0.03027245 |  0.17274472 |  0.03178640 |\n",
       "| Ets2 | 20.94074853 | 21.50369210 | 10.93750 | 12.0765832 | 13.05707584 |  0.26236125 |  7.21689060 |  0.85823268 |\n",
       "| Psmg1 |  5.42790876 |  6.42201835 |  5.46875 |  4.4673540 |  4.61297889 |  0.92835520 |  2.72552783 |  0.89001907 |\n",
       "| Brwd1 | 64.74445612 | 71.52606847 | 78.28125 | 48.7972509 | 50.97732604 | 18.62764884 | 33.22456814 | 13.57279085 |\n",
       "| Hmgn1 | 21.11595001 | 22.26448870 | 25.46875 | 15.8075601 | 15.08991400 |  2.57315843 | 10.38387716 |  3.33757152 |\n",
       "| Wrb | 15.00392118 | 18.12486015 | 19.84375 | 10.0638193 | 10.63330727 |  1.26135217 |  5.96928983 |  1.49396058 |\n",
       "| Lca5l | 14.78533647 | 18.16961289 | 20.46875 | 10.2110947 |  9.92963253 |  0.49445005 |  4.97120921 |  2.22504768 |\n",
       "| Sh3bgr |  0.74418915 |  0.87267845 |  2.03125 |  0.4909180 |  0.15637217 |  0.02018163 |  0.23032630 |  0.00000000 |\n",
       "| B3galt5 | 25.05381188 | 21.21279928 | 22.18750 | 14.2857143 | 21.81391712 | 22.10898083 | 10.07677543 |  5.94405594 |\n",
       "| Igsf5 |  0.24027632 |  0.19019915 |  2.50000 |  0.1963672 |  0.07818608 |  0.30272452 |  0.17274472 |  0.00000000 |\n",
       "| Itgb2l |  0.01668586 |  0.02237637 |  0.31250 |  0.0000000 |  0.00000000 |  0.01009082 |  0.01919386 |  0.00000000 |\n",
       "| Dscam | 67.47259348 | 92.15708212 | 99.37500 | 97.7417771 | 44.17513683 |  4.26841574 | 16.08445298 |  2.32040687 |\n",
       "| Bace2 |  1.22807896 |  1.98030879 |  0.62500 |  0.5891016 |  0.86004691 |  0.34308779 |  0.51823417 |  0.00000000 |\n",
       "| Fam3b |  0.16518997 |  0.16782278 |  0.00000 |  0.0981836 |  0.15637217 |  0.01009082 |  0.01919386 |  0.00000000 |\n",
       "| Tmprss2 |  0.05005757 |  0.04475274 |  0.15625 |  0.0000000 |  0.07818608 |  0.04036327 |  0.05758157 |  0.03178640 |\n",
       "| Ripk4 |  1.07123192 |  0.92861938 |  2.34375 |  0.4909180 |  0.62548866 |  0.29263370 |  0.74856046 |  0.03178640 |\n",
       "| Prdm15 | 21.29949442 | 26.51599910 | 30.78125 | 14.7275405 | 13.68256450 |  2.13925328 |  8.69481766 |  3.59186268 |\n",
       "\n"
      ],
      "text/plain": [
       "            GABAergic    Glutamatergic BFCN     OPC        Doublet    \n",
       "Lipi         0.045051810  0.13425822    0.15625  0.0000000  0.07818608\n",
       "Rbm11        5.684870935  6.31013650   19.06250  7.3637703  5.08209539\n",
       "Hspa13      13.639018204 16.17811591   22.34375 12.6165930 10.71149335\n",
       "Samsn1       0.320368424  0.71604386    1.25000  0.3436426  6.33307271\n",
       "Nrip1       23.236722231 27.38867756   62.81250 21.8949435 34.40187647\n",
       "Usp25       29.585690210 38.28597002   50.46875 24.5949926 26.58326818\n",
       "Cxadr       26.480452520 32.13246811   36.40625 18.9494354 19.07740422\n",
       "Btg3        11.720144833 12.27343925   12.96875  7.8055965  7.97498045\n",
       "D16Ertd472e  2.491198211  4.02774670    1.71875  4.4182622  5.47302580\n",
       "Chodl        1.957250838  1.29782949    0.46875  0.9327442  0.93823299\n",
       "Ncam2       70.671271963 85.19803088   77.65625 94.4526264 62.00156372\n",
       "Mrpl39       6.912949892  8.50302081    9.68750  5.6455572  5.16028147\n",
       "Jam2         3.670888188  5.28082345    3.59375 25.4295533  6.88037529\n",
       "Atp5j       26.947656472 30.49899306   36.25000 21.6003927 20.56293980\n",
       "Gabpa       12.921526422 15.05929738   17.18750 11.5856652 10.63330727\n",
       "App         91.929051743 94.55135377   97.50000 68.5321551 78.81157154\n",
       "Cyyr1        0.545627472  1.76773327    9.53125  0.3436426  0.93823299\n",
       "Adamts1      0.892693264  2.31595435    0.78125  5.1055474  2.42376857\n",
       "Adamts5      1.159666950  1.23070038    0.62500  6.2346588  0.86004691\n",
       "N6amt1       9.250638234 10.41620049   10.62500  7.2655866  4.76935106\n",
       "Rwdd2b       1.716974521  2.10337883    2.03125  1.7182131  1.25097733\n",
       "Usp16       31.614690227 38.21884090   42.50000 31.5660285 23.76856919\n",
       "Cct8        18.317732059 22.53300515   27.65625 14.7275405 13.60437842\n",
       "Bach1        7.962490197 10.36025957   19.84375  8.0510555  9.61688819\n",
       "Grik1       40.539954281 42.85074961   40.00000 52.5773196 34.48006255\n",
       "Cldn17       0.001668586  0.00000000    0.00000  0.0000000  0.00000000\n",
       "Cldn8        0.008342928  0.02237637    0.00000  0.0000000  0.00000000\n",
       "Krtap26-1    0.000000000  0.00000000    0.15625  0.0000000  0.00000000\n",
       "Krtap13-1    0.000000000  0.00000000    0.00000  0.0000000  0.00000000\n",
       "Krtap13      0.000000000  0.00000000    0.00000  0.0000000  0.00000000\n",
       "⋮           ⋮            ⋮             ⋮        ⋮          ⋮          \n",
       "Cbr1        15.25754618  18.06891922   29.53125 12.6165930 11.10242377\n",
       "Cbr3         5.11254609   1.82367420    5.00000  7.7565047  3.90930414\n",
       "Morc3       23.09989822  28.41799060   39.84375 20.1767305 23.92494136\n",
       "Chaf1b       0.10845806   0.12307004    0.31250  0.0490918  0.23455825\n",
       "Cldn14       0.31202550   0.34683374    0.46875  1.0309278  1.17279124\n",
       "Sim2         0.49890708   0.55940926    0.31250  0.1963672  0.23455825\n",
       "Hlcs        37.80013682  41.86618930   48.75000 29.4550810 29.16340891\n",
       "Ripply3      0.05840049   0.12307004    0.00000  0.0490918  0.07818608\n",
       "Pigp        22.52590479  24.97202954   37.81250 18.6548846 19.15559030\n",
       "Ttc3        96.26737415  97.66166928   98.59375 72.2140403 76.15324472\n",
       "Dyrk1a      56.78363451  65.80890580   70.78125 46.1953854 45.73885848\n",
       "Kcnj6       35.84288599  59.38688745   28.12500 16.8875798 24.78498827\n",
       "Kcnj15       0.01501727   0.11188185    0.00000  0.0000000  0.00000000\n",
       "Erg          0.28199096   0.25732826    0.46875  0.1963672  0.23455825\n",
       "Ets2        20.94074853  21.50369210   10.93750 12.0765832 13.05707584\n",
       "Psmg1        5.42790876   6.42201835    5.46875  4.4673540  4.61297889\n",
       "Brwd1       64.74445612  71.52606847   78.28125 48.7972509 50.97732604\n",
       "Hmgn1       21.11595001  22.26448870   25.46875 15.8075601 15.08991400\n",
       "Wrb         15.00392118  18.12486015   19.84375 10.0638193 10.63330727\n",
       "Lca5l       14.78533647  18.16961289   20.46875 10.2110947  9.92963253\n",
       "Sh3bgr       0.74418915   0.87267845    2.03125  0.4909180  0.15637217\n",
       "B3galt5     25.05381188  21.21279928   22.18750 14.2857143 21.81391712\n",
       "Igsf5        0.24027632   0.19019915    2.50000  0.1963672  0.07818608\n",
       "Itgb2l       0.01668586   0.02237637    0.31250  0.0000000  0.00000000\n",
       "Dscam       67.47259348  92.15708212   99.37500 97.7417771 44.17513683\n",
       "Bace2        1.22807896   1.98030879    0.62500  0.5891016  0.86004691\n",
       "Fam3b        0.16518997   0.16782278    0.00000  0.0981836  0.15637217\n",
       "Tmprss2      0.05005757   0.04475274    0.15625  0.0000000  0.07818608\n",
       "Ripk4        1.07123192   0.92861938    2.34375  0.4909180  0.62548866\n",
       "Prdm15      21.29949442  26.51599910   30.78125 14.7275405 13.68256450\n",
       "            Oligodendrocyte Astrocyte   Microglia  \n",
       "Lipi         0.00000000      0.03838772  0.00000000\n",
       "Rbm11        1.06962664      1.84261036  0.12714558\n",
       "Hspa13       1.68516650      8.00383877  1.52574698\n",
       "Samsn1       0.02018163      0.32629559 11.34774317\n",
       "Nrip1        9.67709384     18.11900192 39.06547997\n",
       "Usp25       15.46922301     19.25143954 11.79275270\n",
       "Cxadr        0.40363269      8.36852207  0.63572791\n",
       "Btg3         0.51463169      4.60652591  1.23966942\n",
       "D16Ertd472e 13.62260343      2.47600768  0.60394151\n",
       "Chodl        0.05045409      0.63339731  0.03178640\n",
       "Ncam2       63.84460141     51.22840691  2.19326128\n",
       "Mrpl39       1.87689203      4.06909789  1.65289256\n",
       "Jam2         0.87790111     16.25719770  5.84869676\n",
       "Atp5j        5.43895055     19.04030710  4.41830896\n",
       "Gabpa        3.38042381      7.86948177  2.98792117\n",
       "App         75.43895055     35.27831094  9.47234584\n",
       "Cyyr1        0.07063572      0.13435701  0.00000000\n",
       "Adamts1      3.88496468      1.43953935  0.34965035\n",
       "Adamts5      0.08072654      0.42226488  0.06357279\n",
       "N6amt1       0.72653885      4.22264875  1.08073744\n",
       "Rwdd2b       0.34308779      1.03646833  0.19071837\n",
       "Usp16        8.68819374     16.08445298  5.88048315\n",
       "Cct8         3.01715439      9.23224568  2.63827082\n",
       "Bach1        2.69424823      4.93282150  8.23267641\n",
       "Grik1        9.79818365     11.74664107  1.36681500\n",
       "Cldn17       0.03027245      0.00000000  0.00000000\n",
       "Cldn8        0.04036327      0.01919386  0.00000000\n",
       "Krtap26-1    0.00000000      0.00000000  0.00000000\n",
       "Krtap13-1    0.00000000      0.00000000  0.00000000\n",
       "Krtap13      0.00000000      0.00000000  0.00000000\n",
       "⋮           ⋮               ⋮           ⋮          \n",
       "Cbr1         2.09889001      8.56046065  1.65289256\n",
       "Cbr3         0.06054490      6.14203455  0.66751430\n",
       "Morc3        4.48032291     14.45297505 18.05467260\n",
       "Chaf1b       0.11099899      0.05758157  0.00000000\n",
       "Cldn14       4.52068618      0.46065259  0.06357279\n",
       "Sim2         0.00000000      0.11516315  0.09535919\n",
       "Hlcs         6.04439960     22.05374280  5.05403687\n",
       "Ripply3      0.01009082      0.03838772  0.00000000\n",
       "Pigp         4.94450050     16.14203455  2.47933884\n",
       "Ttc3        11.85671039     39.55854127  8.32803560\n",
       "Dyrk1a      16.97275479     33.93474088 19.80292435\n",
       "Kcnj6        0.50454087      7.83109405  1.11252384\n",
       "Kcnj15       0.01009082      0.00000000  0.00000000\n",
       "Erg          0.03027245      0.17274472  0.03178640\n",
       "Ets2         0.26236125      7.21689060  0.85823268\n",
       "Psmg1        0.92835520      2.72552783  0.89001907\n",
       "Brwd1       18.62764884     33.22456814 13.57279085\n",
       "Hmgn1        2.57315843     10.38387716  3.33757152\n",
       "Wrb          1.26135217      5.96928983  1.49396058\n",
       "Lca5l        0.49445005      4.97120921  2.22504768\n",
       "Sh3bgr       0.02018163      0.23032630  0.00000000\n",
       "B3galt5     22.10898083     10.07677543  5.94405594\n",
       "Igsf5        0.30272452      0.17274472  0.00000000\n",
       "Itgb2l       0.01009082      0.01919386  0.00000000\n",
       "Dscam        4.26841574     16.08445298  2.32040687\n",
       "Bace2        0.34308779      0.51823417  0.00000000\n",
       "Fam3b        0.01009082      0.01919386  0.00000000\n",
       "Tmprss2      0.04036327      0.05758157  0.03178640\n",
       "Ripk4        0.29263370      0.74856046  0.03178640\n",
       "Prdm15       2.13925328      8.69481766  3.59186268"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pctExp <- Percent_Expressing(sobj, features = tri16Genes, group_by = \"broad_celltypes\")\n",
    "pctExp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8482d943-9df3-4ddd-a009-5d76a2f6eb33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Doublet</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Lipi</th><td> 0.04505181</td><td> 0.1342582</td><td> 0.15625</td><td> 0.0000000</td><td> 0.07818608</td><td> 0.00000000</td><td> 0.03838772</td><td> 0.0000000</td></tr>\n",
       "\t<tr><th scope=row>Rbm11</th><td> 5.68487093</td><td> 6.3101365</td><td>19.06250</td><td> 7.3637703</td><td> 5.08209539</td><td> 1.06962664</td><td> 1.84261036</td><td> 0.1271456</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>13.63901820</td><td>16.1781159</td><td>22.34375</td><td>12.6165930</td><td>10.71149335</td><td> 1.68516650</td><td> 8.00383877</td><td> 1.5257470</td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td> 0.32036842</td><td> 0.7160439</td><td> 1.25000</td><td> 0.3436426</td><td> 6.33307271</td><td> 0.02018163</td><td> 0.32629559</td><td>11.3477432</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td>23.23672223</td><td>27.3886776</td><td>62.81250</td><td>21.8949435</td><td>34.40187647</td><td> 9.67709384</td><td>18.11900192</td><td>39.0654800</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td>29.58569021</td><td>38.2859700</td><td>50.46875</td><td>24.5949926</td><td>26.58326818</td><td>15.46922301</td><td>19.25143954</td><td>11.7927527</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Doublet & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tLipi &  0.04505181 &  0.1342582 &  0.15625 &  0.0000000 &  0.07818608 &  0.00000000 &  0.03838772 &  0.0000000\\\\\n",
       "\tRbm11 &  5.68487093 &  6.3101365 & 19.06250 &  7.3637703 &  5.08209539 &  1.06962664 &  1.84261036 &  0.1271456\\\\\n",
       "\tHspa13 & 13.63901820 & 16.1781159 & 22.34375 & 12.6165930 & 10.71149335 &  1.68516650 &  8.00383877 &  1.5257470\\\\\n",
       "\tSamsn1 &  0.32036842 &  0.7160439 &  1.25000 &  0.3436426 &  6.33307271 &  0.02018163 &  0.32629559 & 11.3477432\\\\\n",
       "\tNrip1 & 23.23672223 & 27.3886776 & 62.81250 & 21.8949435 & 34.40187647 &  9.67709384 & 18.11900192 & 39.0654800\\\\\n",
       "\tUsp25 & 29.58569021 & 38.2859700 & 50.46875 & 24.5949926 & 26.58326818 & 15.46922301 & 19.25143954 & 11.7927527\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 8\n",
       "\n",
       "| <!--/--> | GABAergic &lt;dbl&gt; | Glutamatergic &lt;dbl&gt; | BFCN &lt;dbl&gt; | OPC &lt;dbl&gt; | Doublet &lt;dbl&gt; | Oligodendrocyte &lt;dbl&gt; | Astrocyte &lt;dbl&gt; | Microglia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| Lipi |  0.04505181 |  0.1342582 |  0.15625 |  0.0000000 |  0.07818608 |  0.00000000 |  0.03838772 |  0.0000000 |\n",
       "| Rbm11 |  5.68487093 |  6.3101365 | 19.06250 |  7.3637703 |  5.08209539 |  1.06962664 |  1.84261036 |  0.1271456 |\n",
       "| Hspa13 | 13.63901820 | 16.1781159 | 22.34375 | 12.6165930 | 10.71149335 |  1.68516650 |  8.00383877 |  1.5257470 |\n",
       "| Samsn1 |  0.32036842 |  0.7160439 |  1.25000 |  0.3436426 |  6.33307271 |  0.02018163 |  0.32629559 | 11.3477432 |\n",
       "| Nrip1 | 23.23672223 | 27.3886776 | 62.81250 | 21.8949435 | 34.40187647 |  9.67709384 | 18.11900192 | 39.0654800 |\n",
       "| Usp25 | 29.58569021 | 38.2859700 | 50.46875 | 24.5949926 | 26.58326818 | 15.46922301 | 19.25143954 | 11.7927527 |\n",
       "\n"
      ],
      "text/plain": [
       "       GABAergic   Glutamatergic BFCN     OPC        Doublet    \n",
       "Lipi    0.04505181  0.1342582     0.15625  0.0000000  0.07818608\n",
       "Rbm11   5.68487093  6.3101365    19.06250  7.3637703  5.08209539\n",
       "Hspa13 13.63901820 16.1781159    22.34375 12.6165930 10.71149335\n",
       "Samsn1  0.32036842  0.7160439     1.25000  0.3436426  6.33307271\n",
       "Nrip1  23.23672223 27.3886776    62.81250 21.8949435 34.40187647\n",
       "Usp25  29.58569021 38.2859700    50.46875 24.5949926 26.58326818\n",
       "       Oligodendrocyte Astrocyte   Microglia \n",
       "Lipi    0.00000000      0.03838772  0.0000000\n",
       "Rbm11   1.06962664      1.84261036  0.1271456\n",
       "Hspa13  1.68516650      8.00383877  1.5257470\n",
       "Samsn1  0.02018163      0.32629559 11.3477432\n",
       "Nrip1   9.67709384     18.11900192 39.0654800\n",
       "Usp25  15.46922301     19.25143954 11.7927527"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>90</li><li>8</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 90\n",
       "\\item 8\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 90\n",
       "2. 8\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 90  8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "56"
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       "56"
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       "56"
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      "text/plain": [
       "[1] 56"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(pctExp)\n",
    "dim(pctExp)\n",
    "\n",
    "# remove genes that dont have pct exp in @ least 1 broadCT\n",
    "\n",
    "keepgenes <- rownames(pctExp[apply(pctExp, 1, max) >= 10, ])\n",
    "length(keepgenes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "716a428b-1854-4def-bd77-7fb614bd2bce",
   "metadata": {},
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in eval(expr, envir, enclos): object 'plotMtx' not found\n",
     "output_type": "error",
     "traceback": [
      "Error in eval(expr, envir, enclos): object 'plotMtx' not found\nTraceback:\n"
     ]
    }
   ],
   "source": [
    "### LOG2FOLDCHANGE ###\n",
    "plotMtx_pctexp <- plotMtx[which(rownames(plotMtx) %in% keepgenes),]\n",
    "dim(plotMtx_pctexp)\n",
    "\n",
    "f1 <- colorRamp2(seq(min(plotMtx_pctexp), max(plotMtx_pctexp), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "ht <- Heatmap(as.matrix(plotMtx_pctexp), name=paste0(\"log2FoldChange\"), column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", pairwise, \"\\n(10% min exp)\"),\n",
    "              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx_pctexp),\n",
    "              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx_pctexp)*unit(10, \"mm\"))\n",
    "ht <- draw(ht)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "1e31459b-508a-4168-aef3-239ceb80758e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style>\n",
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       "<ol class=list-inline><li>50</li><li>7</li></ol>\n"
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       "\\begin{enumerate*}\n",
       "\\item 50\n",
       "\\item 7\n",
       "\\end{enumerate*}\n"
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       "1. 50\n",
       "2. 7\n",
       "\n",
       "\n"
      ],
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       "[1] 50  7"
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    {
     "data": {
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StfeTXZZ/KT3eMWT5is2qSVlXmjBvJi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\nnx39btZsEBGRaXAWJ5i7QcTlEMel8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5Ll3FPukR6ucdO6NH9SZLt3MTHB4AakOw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\njF9U1aMkAMBfK+XfuigoO3JMAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 720,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### LOG10FOLDCHANGE ###\n",
    "plotMtx_pctexp <- plotMtx_log10[which(rownames(plotMtx_log10) %in% keepgenes),]\n",
    "dim(plotMtx_pctexp)\n",
    "\n",
    "f1 <- colorRamp2(seq(min(plotMtx_pctexp), max(plotMtx_pctexp), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "ht <- Heatmap(as.matrix(plotMtx_pctexp), name=paste0(\"log10FoldChange\"), column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", pairwise, \"\\n(10% min exp)\"),\n",
    "              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx_pctexp),\n",
    "              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx_pctexp)*unit(10, \"mm\"))\n",
    "ht <- draw(ht)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "c1704ec5-385e-436b-9a96-9fd27f798aee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>50</li><li>7</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 50\n",
       "\\item 7\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 50\n",
       "2. 7\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 50  7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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WbBuImqDa2sLepryYulxXy4f/NBZJp4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t3MLae/3VbMGfDgA0Ggh2AAD894udrQxd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\n1BB+aUlJSfSt8XihUEhJSYzsSqOkb1H4eLn2I5YsEXSys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HrgHZmbm4shFQAAiBYKOwCJZD14ZEu5mE1ezv2XHbkTl5otIEF2atydI8v6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\noZERrsJgMDgoEgDAcf4LjSx/CKNuxeQAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 720,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### ZSCORE LOG2FC ###\n",
    "plotMtx_pctexp <- plotMtx_zsc[which(rownames(plotMtx_zsc) %in% keepgenes),]\n",
    "dim(plotMtx_pctexp)\n",
    "\n",
    "f1 <- colorRamp2(seq(min(plotMtx_pctexp), max(plotMtx_pctexp), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "ht <- Heatmap(as.matrix(plotMtx_pctexp), name=paste0(\"Z-score log2FoldChange\"), column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", pairwise, \"\\n(10% min exp)\"),\n",
    "              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx_pctexp),\n",
    "              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx_pctexp)*unit(10, \"mm\"))\n",
    "ht <- draw(ht)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebd58383-e80a-405c-bf61-d2abcc4f4411",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "### adding in \"*\" for padj <= 0.05 DEGs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7654e727-4264-4b0c-8600-3b4c11fcc3ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"STARTING: Dp16_old-Dp16_yng\"\n",
      "[1] \"GABAergic\"\n",
      "[1] 76  4\n",
      "[1] \"Glutamatergic\"\n",
      "[1] 67  4\n",
      "[1] \"BFCN\"\n",
      "[1] 27  4\n",
      "[1] \"OPC\"\n",
      "[1] 35  4\n",
      "[1] \"Oligodendrocyte\"\n",
      "[1] 55  4\n",
      "[1] \"Astrocyte\"\n",
      "[1] 44  4\n",
      "[1] \"Microglia\"\n",
      "[1] 18  4\n",
      "[1] \"done going through celltypes\"\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Lipi</th><td> 0.0000000</td><td> 0.00000000</td><td> 0.0000000</td><td> 0.0000000</td><td> 0.00000000</td><td>0.0000000</td><td>0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Rbm11</th><td> 0.2086911</td><td> 0.03074049</td><td> 0.0000000</td><td> 0.0000000</td><td>-0.21774837</td><td>0.0000000</td><td>0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>-0.1536817</td><td>-0.09130245</td><td> 0.0000000</td><td> 0.0000000</td><td> 0.43405623</td><td>0.2658920</td><td>0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td> 0.5559112</td><td> 0.00000000</td><td> 0.0000000</td><td> 0.0000000</td><td> 0.00000000</td><td>0.0000000</td><td>0.47601835</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td> 0.1662311</td><td> 0.23725786</td><td>-0.2332674</td><td>-0.1201510</td><td>-0.37678185</td><td>0.2372267</td><td>0.05470513</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td> 0.3303855</td><td> 0.20754696</td><td> 0.1531498</td><td> 0.4153594</td><td>-0.02298244</td><td>0.5277448</td><td>0.51228537</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tLipi &  0.0000000 &  0.00000000 &  0.0000000 &  0.0000000 &  0.00000000 & 0.0000000 & 0.00000000\\\\\n",
       "\tRbm11 &  0.2086911 &  0.03074049 &  0.0000000 &  0.0000000 & -0.21774837 & 0.0000000 & 0.00000000\\\\\n",
       "\tHspa13 & -0.1536817 & -0.09130245 &  0.0000000 &  0.0000000 &  0.43405623 & 0.2658920 & 0.00000000\\\\\n",
       "\tSamsn1 &  0.5559112 &  0.00000000 &  0.0000000 &  0.0000000 &  0.00000000 & 0.0000000 & 0.47601835\\\\\n",
       "\tNrip1 &  0.1662311 &  0.23725786 & -0.2332674 & -0.1201510 & -0.37678185 & 0.2372267 & 0.05470513\\\\\n",
       "\tUsp25 &  0.3303855 &  0.20754696 &  0.1531498 &  0.4153594 & -0.02298244 & 0.5277448 & 0.51228537\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 7\n",
       "\n",
       "| <!--/--> | GABAergic &lt;dbl&gt; | Glutamatergic &lt;dbl&gt; | BFCN &lt;dbl&gt; | OPC &lt;dbl&gt; | Oligodendrocyte &lt;dbl&gt; | Astrocyte &lt;dbl&gt; | Microglia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| Lipi |  0.0000000 |  0.00000000 |  0.0000000 |  0.0000000 |  0.00000000 | 0.0000000 | 0.00000000 |\n",
       "| Rbm11 |  0.2086911 |  0.03074049 |  0.0000000 |  0.0000000 | -0.21774837 | 0.0000000 | 0.00000000 |\n",
       "| Hspa13 | -0.1536817 | -0.09130245 |  0.0000000 |  0.0000000 |  0.43405623 | 0.2658920 | 0.00000000 |\n",
       "| Samsn1 |  0.5559112 |  0.00000000 |  0.0000000 |  0.0000000 |  0.00000000 | 0.0000000 | 0.47601835 |\n",
       "| Nrip1 |  0.1662311 |  0.23725786 | -0.2332674 | -0.1201510 | -0.37678185 | 0.2372267 | 0.05470513 |\n",
       "| Usp25 |  0.3303855 |  0.20754696 |  0.1531498 |  0.4153594 | -0.02298244 | 0.5277448 | 0.51228537 |\n",
       "\n"
      ],
      "text/plain": [
       "       GABAergic  Glutamatergic BFCN       OPC        Oligodendrocyte Astrocyte\n",
       "Lipi    0.0000000  0.00000000    0.0000000  0.0000000  0.00000000     0.0000000\n",
       "Rbm11   0.2086911  0.03074049    0.0000000  0.0000000 -0.21774837     0.0000000\n",
       "Hspa13 -0.1536817 -0.09130245    0.0000000  0.0000000  0.43405623     0.2658920\n",
       "Samsn1  0.5559112  0.00000000    0.0000000  0.0000000  0.00000000     0.0000000\n",
       "Nrip1   0.1662311  0.23725786   -0.2332674 -0.1201510 -0.37678185     0.2372267\n",
       "Usp25   0.3303855  0.20754696    0.1531498  0.4153594 -0.02298244     0.5277448\n",
       "       Microglia \n",
       "Lipi   0.00000000\n",
       "Rbm11  0.00000000\n",
       "Hspa13 0.00000000\n",
       "Samsn1 0.47601835\n",
       "Nrip1  0.05470513\n",
       "Usp25  0.51228537"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<style>\n",
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       "</style>\n",
       "<ol class=list-inline><li>114</li><li>7</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 114\n",
       "\\item 7\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 114\n",
       "2. 7\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 114   7"
      ]
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    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Lipi</th><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>Rbm11</th><td>No</td><td>No</td><td>0 </td><td>0 </td><td>No</td><td>0 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>No</td><td>No</td><td>0 </td><td>0 </td><td>No</td><td>No</td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td>No</td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>No</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\tLipi & 0  & 0  & 0  & 0  & 0  & 0  & 0 \\\\\n",
       "\tRbm11 & No & No & 0  & 0  & No & 0  & 0 \\\\\n",
       "\tHspa13 & No & No & 0  & 0  & No & No & 0 \\\\\n",
       "\tSamsn1 & No & 0  & 0  & 0  & 0  & 0  & No\\\\\n",
       "\tNrip1 & No & No & No & No & No & No & No\\\\\n",
       "\tUsp25 & No & No & No & No & No & No & No\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 7\n",
       "\n",
       "| <!--/--> | GABAergic &lt;chr&gt; | Glutamatergic &lt;chr&gt; | BFCN &lt;chr&gt; | OPC &lt;chr&gt; | Oligodendrocyte &lt;chr&gt; | Astrocyte &lt;chr&gt; | Microglia &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| Lipi | 0  | 0  | 0  | 0  | 0  | 0  | 0  |\n",
       "| Rbm11 | No | No | 0  | 0  | No | 0  | 0  |\n",
       "| Hspa13 | No | No | 0  | 0  | No | No | 0  |\n",
       "| Samsn1 | No | 0  | 0  | 0  | 0  | 0  | No |\n",
       "| Nrip1 | No | No | No | No | No | No | No |\n",
       "| Usp25 | No | No | No | No | No | No | No |\n",
       "\n"
      ],
      "text/plain": [
       "       GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
       "Lipi   0         0             0    0   0               0         0        \n",
       "Rbm11  No        No            0    0   No              0         0        \n",
       "Hspa13 No        No            0    0   No              No        0        \n",
       "Samsn1 No        0             0    0   0               0         No       \n",
       "Nrip1  No        No            No   No  No              No        No       \n",
       "Usp25  No        No            No   No  No              No        No       "
      ]
     },
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     "output_type": "display_data"
    },
    {
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       "<style>\n",
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       "</style>\n",
       "<ol class=list-inline><li>114</li><li>7</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 114\n",
       "\\item 7\n",
       "\\end{enumerate*}\n"
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      "text/markdown": [
       "1. 114\n",
       "2. 7\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 114   7"
      ]
     },
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
      "Ets2       Yes            No    0   0               0        No         0\n",
      "     GABAergic Glutamatergic BFCN OPC Oligodendrocyte  Astrocyte Microglia\n",
      "Ets2 -0.397393     -0.290098    0   0               0 -0.4516577         0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“\u001b[1m\u001b[22mThe following features were omitted as they were not found:\n",
      "\u001b[36mℹ\u001b[39m \u001b[32mmmu-miR-99a, mmu-let-7c-1, mmu-miR-125b-2, Prss7, mmu-miR-155, Zfp294, Orf63,\u001b[39m\n",
      "  \u001b[32mGm312, Krtap16, Krtap16-7, Krtap16-4, Krtap8-2, Sfrs15, 2610039C10Rik,\u001b[39m\n",
      "  \u001b[32m4931408A02Rik, 1110004E09Rik, 1810007M14Rik, 4930563D23Rik, mmu-miR-802,\u001b[39m\n",
      "  \u001b[32mDopey2, Dscr3, Mx2, 5830404H04Rik, and Zfp295\u001b[39m”\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"keepgenes\"\n",
      " [1] \"Rbm11\"       \"Hspa13\"      \"Samsn1\"      \"Nrip1\"       \"Usp25\"      \n",
      " [6] \"Cxadr\"       \"Btg3\"        \"D16Ertd472e\" \"Ncam2\"       \"Jam2\"       \n",
      "[11] \"Atp5j\"       \"Gabpa\"       \"App\"         \"N6amt1\"      \"Usp16\"      \n",
      "[16] \"Cct8\"        \"Bach1\"       \"Grik1\"       \"Tiam1\"       \"Sod1\"       \n",
      "[21] \"Hunk\"        \"Urb1\"        \"Synj1\"       \"Olig2\"       \"Olig1\"      \n",
      "[26] \"Ifnar2\"      \"Ifnar1\"      \"Ifngr2\"      \"Tmem50b\"     \"Gart\"       \n",
      "[31] \"Son\"         \"Donson\"      \"Atp5o\"       \"Cryzl1\"      \"Itsn1\"      \n",
      "[36] \"Mrps6\"       \"Slc5a3\"      \"Rcan1\"       \"Clic6\"       \"Runx1\"      \n",
      "[41] \"Setd4\"       \"Cbr1\"        \"Morc3\"       \"Hlcs\"        \"Pigp\"       \n",
      "[46] \"Ttc3\"        \"Dyrk1a\"      \"Kcnj6\"       \"Ets2\"        \"Brwd1\"      \n",
      "[51] \"Hmgn1\"       \"Wrb\"         \"Lca5l\"       \"B3galt5\"     \"Dscam\"      \n",
      "[56] \"Prdm15\"     \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Rbm11</th><td> 0.2086911</td><td> 0.03074049</td><td> 0.00000000</td><td> 0.0000000</td><td>-0.21774837</td><td>0.0000000</td><td>0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>-0.1536817</td><td>-0.09130245</td><td> 0.00000000</td><td> 0.0000000</td><td> 0.43405623</td><td>0.2658920</td><td>0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td> 0.5559112</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.0000000</td><td> 0.00000000</td><td>0.0000000</td><td>0.47601835</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td> 0.1662311</td><td> 0.23725786</td><td>-0.23326744</td><td>-0.1201510</td><td>-0.37678185</td><td>0.2372267</td><td>0.05470513</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td> 0.3303855</td><td> 0.20754696</td><td> 0.15314983</td><td> 0.4153594</td><td>-0.02298244</td><td>0.5277448</td><td>0.51228537</td></tr>\n",
       "\t<tr><th scope=row>Cxadr</th><td> 0.4070433</td><td> 0.45291148</td><td> 0.04874068</td><td> 0.2274803</td><td> 1.84844040</td><td>0.3907145</td><td>0.00000000</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tRbm11 &  0.2086911 &  0.03074049 &  0.00000000 &  0.0000000 & -0.21774837 & 0.0000000 & 0.00000000\\\\\n",
       "\tHspa13 & -0.1536817 & -0.09130245 &  0.00000000 &  0.0000000 &  0.43405623 & 0.2658920 & 0.00000000\\\\\n",
       "\tSamsn1 &  0.5559112 &  0.00000000 &  0.00000000 &  0.0000000 &  0.00000000 & 0.0000000 & 0.47601835\\\\\n",
       "\tNrip1 &  0.1662311 &  0.23725786 & -0.23326744 & -0.1201510 & -0.37678185 & 0.2372267 & 0.05470513\\\\\n",
       "\tUsp25 &  0.3303855 &  0.20754696 &  0.15314983 &  0.4153594 & -0.02298244 & 0.5277448 & 0.51228537\\\\\n",
       "\tCxadr &  0.4070433 &  0.45291148 &  0.04874068 &  0.2274803 &  1.84844040 & 0.3907145 & 0.00000000\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 7\n",
       "\n",
       "| <!--/--> | GABAergic &lt;dbl&gt; | Glutamatergic &lt;dbl&gt; | BFCN &lt;dbl&gt; | OPC &lt;dbl&gt; | Oligodendrocyte &lt;dbl&gt; | Astrocyte &lt;dbl&gt; | Microglia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| Rbm11 |  0.2086911 |  0.03074049 |  0.00000000 |  0.0000000 | -0.21774837 | 0.0000000 | 0.00000000 |\n",
       "| Hspa13 | -0.1536817 | -0.09130245 |  0.00000000 |  0.0000000 |  0.43405623 | 0.2658920 | 0.00000000 |\n",
       "| Samsn1 |  0.5559112 |  0.00000000 |  0.00000000 |  0.0000000 |  0.00000000 | 0.0000000 | 0.47601835 |\n",
       "| Nrip1 |  0.1662311 |  0.23725786 | -0.23326744 | -0.1201510 | -0.37678185 | 0.2372267 | 0.05470513 |\n",
       "| Usp25 |  0.3303855 |  0.20754696 |  0.15314983 |  0.4153594 | -0.02298244 | 0.5277448 | 0.51228537 |\n",
       "| Cxadr |  0.4070433 |  0.45291148 |  0.04874068 |  0.2274803 |  1.84844040 | 0.3907145 | 0.00000000 |\n",
       "\n"
      ],
      "text/plain": [
       "       GABAergic  Glutamatergic BFCN        OPC        Oligodendrocyte\n",
       "Rbm11   0.2086911  0.03074049    0.00000000  0.0000000 -0.21774837    \n",
       "Hspa13 -0.1536817 -0.09130245    0.00000000  0.0000000  0.43405623    \n",
       "Samsn1  0.5559112  0.00000000    0.00000000  0.0000000  0.00000000    \n",
       "Nrip1   0.1662311  0.23725786   -0.23326744 -0.1201510 -0.37678185    \n",
       "Usp25   0.3303855  0.20754696    0.15314983  0.4153594 -0.02298244    \n",
       "Cxadr   0.4070433  0.45291148    0.04874068  0.2274803  1.84844040    \n",
       "       Astrocyte Microglia \n",
       "Rbm11  0.0000000 0.00000000\n",
       "Hspa13 0.2658920 0.00000000\n",
       "Samsn1 0.0000000 0.47601835\n",
       "Nrip1  0.2372267 0.05470513\n",
       "Usp25  0.5277448 0.51228537\n",
       "Cxadr  0.3907145 0.00000000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Rbm11'</li><li>'Hspa13'</li><li>'Samsn1'</li><li>'Nrip1'</li><li>'Usp25'</li><li>'Cxadr'</li><li>'Btg3'</li><li>'D16Ertd472e'</li><li>'Ncam2'</li><li>'Jam2'</li><li>'Atp5j'</li><li>'Gabpa'</li><li>'App'</li><li>'N6amt1'</li><li>'Usp16'</li><li>'Cct8'</li><li>'Bach1'</li><li>'Grik1'</li><li>'Tiam1'</li><li>'Sod1'</li><li>'Hunk'</li><li>'Urb1'</li><li>'Synj1'</li><li>'Olig2'</li><li>'Olig1'</li><li>'Ifnar2'</li><li>'Ifnar1'</li><li>'Ifngr2'</li><li>'Tmem50b'</li><li>'Gart'</li><li>'Son'</li><li>'Donson'</li><li>'Atp5o'</li><li>'Cryzl1'</li><li>'Itsn1'</li><li>'Mrps6'</li><li>'Slc5a3'</li><li>'Rcan1'</li><li>'Clic6'</li><li>'Runx1'</li><li>'Setd4'</li><li>'Cbr1'</li><li>'Morc3'</li><li>'Hlcs'</li><li>'Pigp'</li><li>'Ttc3'</li><li>'Dyrk1a'</li><li>'Kcnj6'</li><li>'Ets2'</li><li>'Brwd1'</li><li>'Hmgn1'</li><li>'Wrb'</li><li>'Lca5l'</li><li>'B3galt5'</li><li>'Dscam'</li><li>'Prdm15'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Rbm11'\n",
       "\\item 'Hspa13'\n",
       "\\item 'Samsn1'\n",
       "\\item 'Nrip1'\n",
       "\\item 'Usp25'\n",
       "\\item 'Cxadr'\n",
       "\\item 'Btg3'\n",
       "\\item 'D16Ertd472e'\n",
       "\\item 'Ncam2'\n",
       "\\item 'Jam2'\n",
       "\\item 'Atp5j'\n",
       "\\item 'Gabpa'\n",
       "\\item 'App'\n",
       "\\item 'N6amt1'\n",
       "\\item 'Usp16'\n",
       "\\item 'Cct8'\n",
       "\\item 'Bach1'\n",
       "\\item 'Grik1'\n",
       "\\item 'Tiam1'\n",
       "\\item 'Sod1'\n",
       "\\item 'Hunk'\n",
       "\\item 'Urb1'\n",
       "\\item 'Synj1'\n",
       "\\item 'Olig2'\n",
       "\\item 'Olig1'\n",
       "\\item 'Ifnar2'\n",
       "\\item 'Ifnar1'\n",
       "\\item 'Ifngr2'\n",
       "\\item 'Tmem50b'\n",
       "\\item 'Gart'\n",
       "\\item 'Son'\n",
       "\\item 'Donson'\n",
       "\\item 'Atp5o'\n",
       "\\item 'Cryzl1'\n",
       "\\item 'Itsn1'\n",
       "\\item 'Mrps6'\n",
       "\\item 'Slc5a3'\n",
       "\\item 'Rcan1'\n",
       "\\item 'Clic6'\n",
       "\\item 'Runx1'\n",
       "\\item 'Setd4'\n",
       "\\item 'Cbr1'\n",
       "\\item 'Morc3'\n",
       "\\item 'Hlcs'\n",
       "\\item 'Pigp'\n",
       "\\item 'Ttc3'\n",
       "\\item 'Dyrk1a'\n",
       "\\item 'Kcnj6'\n",
       "\\item 'Ets2'\n",
       "\\item 'Brwd1'\n",
       "\\item 'Hmgn1'\n",
       "\\item 'Wrb'\n",
       "\\item 'Lca5l'\n",
       "\\item 'B3galt5'\n",
       "\\item 'Dscam'\n",
       "\\item 'Prdm15'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Rbm11'\n",
       "2. 'Hspa13'\n",
       "3. 'Samsn1'\n",
       "4. 'Nrip1'\n",
       "5. 'Usp25'\n",
       "6. 'Cxadr'\n",
       "7. 'Btg3'\n",
       "8. 'D16Ertd472e'\n",
       "9. 'Ncam2'\n",
       "10. 'Jam2'\n",
       "11. 'Atp5j'\n",
       "12. 'Gabpa'\n",
       "13. 'App'\n",
       "14. 'N6amt1'\n",
       "15. 'Usp16'\n",
       "16. 'Cct8'\n",
       "17. 'Bach1'\n",
       "18. 'Grik1'\n",
       "19. 'Tiam1'\n",
       "20. 'Sod1'\n",
       "21. 'Hunk'\n",
       "22. 'Urb1'\n",
       "23. 'Synj1'\n",
       "24. 'Olig2'\n",
       "25. 'Olig1'\n",
       "26. 'Ifnar2'\n",
       "27. 'Ifnar1'\n",
       "28. 'Ifngr2'\n",
       "29. 'Tmem50b'\n",
       "30. 'Gart'\n",
       "31. 'Son'\n",
       "32. 'Donson'\n",
       "33. 'Atp5o'\n",
       "34. 'Cryzl1'\n",
       "35. 'Itsn1'\n",
       "36. 'Mrps6'\n",
       "37. 'Slc5a3'\n",
       "38. 'Rcan1'\n",
       "39. 'Clic6'\n",
       "40. 'Runx1'\n",
       "41. 'Setd4'\n",
       "42. 'Cbr1'\n",
       "43. 'Morc3'\n",
       "44. 'Hlcs'\n",
       "45. 'Pigp'\n",
       "46. 'Ttc3'\n",
       "47. 'Dyrk1a'\n",
       "48. 'Kcnj6'\n",
       "49. 'Ets2'\n",
       "50. 'Brwd1'\n",
       "51. 'Hmgn1'\n",
       "52. 'Wrb'\n",
       "53. 'Lca5l'\n",
       "54. 'B3galt5'\n",
       "55. 'Dscam'\n",
       "56. 'Prdm15'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Rbm11\"       \"Hspa13\"      \"Samsn1\"      \"Nrip1\"       \"Usp25\"      \n",
       " [6] \"Cxadr\"       \"Btg3\"        \"D16Ertd472e\" \"Ncam2\"       \"Jam2\"       \n",
       "[11] \"Atp5j\"       \"Gabpa\"       \"App\"         \"N6amt1\"      \"Usp16\"      \n",
       "[16] \"Cct8\"        \"Bach1\"       \"Grik1\"       \"Tiam1\"       \"Sod1\"       \n",
       "[21] \"Hunk\"        \"Urb1\"        \"Synj1\"       \"Olig2\"       \"Olig1\"      \n",
       "[26] \"Ifnar2\"      \"Ifnar1\"      \"Ifngr2\"      \"Tmem50b\"     \"Gart\"       \n",
       "[31] \"Son\"         \"Donson\"      \"Atp5o\"       \"Cryzl1\"      \"Itsn1\"      \n",
       "[36] \"Mrps6\"       \"Slc5a3\"      \"Rcan1\"       \"Clic6\"       \"Runx1\"      \n",
       "[41] \"Setd4\"       \"Cbr1\"        \"Morc3\"       \"Hlcs\"        \"Pigp\"       \n",
       "[46] \"Ttc3\"        \"Dyrk1a\"      \"Kcnj6\"       \"Ets2\"        \"Brwd1\"      \n",
       "[51] \"Hmgn1\"       \"Wrb\"         \"Lca5l\"       \"B3galt5\"     \"Dscam\"      \n",
       "[56] \"Prdm15\"     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     GABAergic Glutamatergic BFCN OPC Oligodendrocyte  Astrocyte Microglia\n",
      "Ets2 -0.397393     -0.290098    0   0               0 -0.4516577         0\n",
      "     GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
      "Ets2       Yes            No    0   0               0        No         0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>56</li><li>7</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 56\n",
       "\\item 7\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 56\n",
       "2. 7\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 56  7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>GABAergic</th><th scope=col>Glutamatergic</th><th scope=col>BFCN</th><th scope=col>OPC</th><th scope=col>Oligodendrocyte</th><th scope=col>Astrocyte</th><th scope=col>Microglia</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Rbm11</th><td>No</td><td>No</td><td>0 </td><td>0 </td><td>No</td><td>0 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>No</td><td>No</td><td>0 </td><td>0 </td><td>No</td><td>No</td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td>No</td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>No</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr>\n",
       "\t<tr><th scope=row>Cxadr</th><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>0 </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & GABAergic & Glutamatergic & BFCN & OPC & Oligodendrocyte & Astrocyte & Microglia\\\\\n",
       "  & <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\tRbm11 & No & No & 0  & 0  & No & 0  & 0 \\\\\n",
       "\tHspa13 & No & No & 0  & 0  & No & No & 0 \\\\\n",
       "\tSamsn1 & No & 0  & 0  & 0  & 0  & 0  & No\\\\\n",
       "\tNrip1 & No & No & No & No & No & No & No\\\\\n",
       "\tUsp25 & No & No & No & No & No & No & No\\\\\n",
       "\tCxadr & No & No & No & No & No & No & 0 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 7\n",
       "\n",
       "| <!--/--> | GABAergic &lt;chr&gt; | Glutamatergic &lt;chr&gt; | BFCN &lt;chr&gt; | OPC &lt;chr&gt; | Oligodendrocyte &lt;chr&gt; | Astrocyte &lt;chr&gt; | Microglia &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| Rbm11 | No | No | 0  | 0  | No | 0  | 0  |\n",
       "| Hspa13 | No | No | 0  | 0  | No | No | 0  |\n",
       "| Samsn1 | No | 0  | 0  | 0  | 0  | 0  | No |\n",
       "| Nrip1 | No | No | No | No | No | No | No |\n",
       "| Usp25 | No | No | No | No | No | No | No |\n",
       "| Cxadr | No | No | No | No | No | No | 0  |\n",
       "\n"
      ],
      "text/plain": [
       "       GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
       "Rbm11  No        No            0    0   No              0         0        \n",
       "Hspa13 No        No            0    0   No              No        0        \n",
       "Samsn1 No        0             0    0   0               0         No       \n",
       "Nrip1  No        No            No   No  No              No        No       \n",
       "Usp25  No        No            No   No  No              No        No       \n",
       "Cxadr  No        No            No   No  No              No        0        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p <- \"Dp16_old-Dp16_yng\"\n",
    "\n",
    "print(paste0(\"STARTING: \", p))\n",
    "\n",
    "# grab all pairwise specific deseq files\n",
    "deseq_files <- list.files(DE_PATH, p, full.names = T)\n",
    "\n",
    "celltypes <- unique(sobj$broad_celltypes)\n",
    "celltypes <- celltypes[!celltypes == \"Doublet\"] # rem doublets\n",
    "\n",
    "# df for signif \"*\" in hmap\n",
    "signif_df <- data.frame(matrix(0, ncol = length(celltypes), nrow = length(tri16Genes))) # contains - log2fc, padj, celltype, and signif cols\n",
    "rownames(signif_df) <- tri16Genes\n",
    "colnames(signif_df) <- celltypes\n",
    "\n",
    "# try to make this tri16genes x celltype dims\n",
    "plotMtx <- as.data.frame(matrix(0, ncol = length(celltypes), nrow = length(tri16Genes))) # contains - just log2fc for each celltype\n",
    "rownames(plotMtx) <- tri16Genes\n",
    "colnames(plotMtx) <- celltypes\n",
    "for(ct in celltypes){\n",
    "    print(ct)\n",
    "\n",
    "    # grab the celltype specific deseq file and subset for tri16 genelist\n",
    "    ct_deseq <- read.csv(grep(ct, deseq_files, value = T), row.names = 1)[,c(\"log2FoldChange\",\"padj\")]\n",
    "    ct_deseq_tri16 <- ct_deseq[which(rownames(ct_deseq) %in% tri16Genes),]\n",
    "    ct_deseq_tri16$Celltype <- ct\n",
    "    \n",
    "    ct_deseq_tri16$Signif <- ifelse(ct_deseq_tri16$padj <= 0.05, \"Yes\", \"No\")\n",
    "    print(dim(ct_deseq_tri16))\n",
    "\n",
    "    #pdata <- rbind(pdata, ct_deseq_tri16)\n",
    "    signif_df[rownames(ct_deseq_tri16),ct] <- ifelse(ct_deseq_tri16$padj <= 0.05, \"Yes\", \"No\")\n",
    "    \n",
    "    # just adding log2fc to dataframe without padj and other cols - maybe this will work better?\n",
    "    plotMtx[rownames(ct_deseq_tri16),ct] <- ct_deseq_tri16$log2FoldChange\n",
    "}\n",
    "print(\"done going through celltypes\")\n",
    "\n",
    "### done making plot data (plotMtx) - now on the plotting section ###    \n",
    "# maybe remove genes that have zeros across all celltypes\n",
    "#plotMtx <- plotMtx[rowSums(plotMtx) > 0, ]\n",
    "#dim(plotMtx)\n",
    "#head(plotMtx)\n",
    "head(plotMtx)\n",
    "dim(plotMtx)\n",
    "head(signif_df)\n",
    "dim(signif_df)\n",
    "print(signif_df[\"Ets2\",])\n",
    "print(plotMtx[\"Ets2\",])\n",
    "\n",
    "# applying 10% min exp cutoff (for each gene @ least one ct must have 10% exp)\n",
    "# TODO: do i need to apply the pct exp based on the pairwise comparison??? ex: Dp16_old v. Dp16_yng pct exp?\n",
    "# TODO: something like this? pctExp <- Percent_Expressing(ct_sobj, features = tri16genes, group_by = \"genotype\")\n",
    "pctExp <- Percent_Expressing(sobj, features = tri16Genes, group_by = \"broad_celltypes\")\n",
    "keepgenes <- rownames(pctExp[apply(pctExp, 1, max) >= 10, ])\n",
    "print(\"keepgenes\")\n",
    "print(keepgenes)\n",
    "plotMtx_pctexp <- plotMtx[which(rownames(plotMtx) %in% keepgenes),]\n",
    "head(plotMtx_pctexp)\n",
    "rownames(plotMtx_pctexp)\n",
    "print(plotMtx_pctexp[\"Ets2\",])\n",
    "\n",
    "# subset signif signif_df df to match plotMtx exactly\n",
    "signif_df <- signif_df[which(rownames(signif_df) %in% rownames(plotMtx_pctexp)), ]\n",
    "print(signif_df[\"Ets2\",])\n",
    "dim(signif_df)\n",
    "head(signif_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "368e2f86-b98b-4adf-8c9a-f125619c3fb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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d96Hdnmr6cH56xxny+qMFhTpa8UP1vx\n9+TH956kF7PLOvou062qo2g3etD6xDe+ViovzTRlBbgIUJjsu8JEAACg5P2d06fvgZI83hiL\nEGJdzF5vBfUoDRelY+fiFRLvJT/YZPSMFbsuvMhmtIxvi+vYAQzyTqyqRyv68uzqkU0LHEdo\nq8hTRHk5ObjIwjJKQ62cvQJjvjBoufjTjd0LxxoM7CVM5uLkEZaWG6BlNnmZ7+mHnxuuUEbL\nexa00EZDVoibi0dIVs1qbkBcXvlJO2iwjt2PqvXimtOWJ9g2u44d+4RwBtUZrWMXObvZR3wx\nWHuvLOXaNlcLVYowmZOTLErVtHbbGfWZ4crOzSn8cH3f8qlWWvIyonwkDk4eQXHZQXo2ziv2\nXErMaW/PN3fKD+ZKAoBRQHY72vzjOnZFby/vXTNnrJG6IkWcn8TFK9ZbSdPcZfPZl3n1F8kr\nSz63apyOggQfV9Wdsnq1qwTiAsUIIdZH0Jtbrgqhf1bFKXvOiRdJky+XhtowOxaEEEKo9XCO\nHUIIIYRQD4GJHUIIIYRQD4GJHUIIIYRQD4Fz7BBCCCGEeggcsUMIIYQQ6iEwsUMIIYQQ6iEw\nsUNMs7o/UYeNg5tfRJKioGk61nWlX8SL7L98pFPB2xtH/bznO1nr9pfkYSMIgjDel9nSDmWf\nb/otGKOrKC1MJvEIScupmkxY4Bfd4i7tFD1HjCAIy5DCP1WsOGVPEAS305U/t/n6X+1MhBBC\nDeCTJxCTSaqYKksAAL2i5Gd+dkZS9IWEOxeCtq7oY73myOFVw6XZ29fsc39nZ/+sVlamZYTP\nMncKelsMBFlSXmEQuSwn4+ODM4kfpB0WGUu1LwCmwM5ECKF/HCZ2iMmM10adGlf3suJncnTY\nnnVr/R9eXWNhkHrpUaCVeHuaFVG1m+lB1Rysqamp9Hgudd6t5quWxnmYOwS9JeTH7wra5WbY\ni1QVSF7SvXu5cu05NvNgZyKE0D8OEzvEWjgE5M3m7DGx0Zs41PHsx6Cpi21SQu352t6O6qyD\nh6p/LHxBtFTz1dZZu95W8Jvujzrt1qeuJodIf9PRbT8uS8HORAihfw3OsUOsiJ0y4bDfeH6A\nnFM7Qr7UFp8bRxAEh2ME/cfjgwusNXqLkklkUbmhYzxCE3+280iV9wIOJNKg14z1s/q0mLK0\nUknKje2zrTXlxPlJXGThXsomk9eGvSpoxY75z0OW2Gn1ESFz84r2GWy7KPBZa/Zqje7XmR+3\nabIThJjzjdImm35HzpAgCDbVTe+qXtecBZS8PbPGQVdenI/ELSCjYj7bPy63yc70vPigRbaa\nvYXJpNpOrpnI+BfhIoQQC8HEDrEowbHTR/MDVMZF3vnVcEtB1Hxd/bmhqaLaI8fa6cn8eh6+\nfYq2wYp7+e05zKtbtzIBhC2th/1OvRu0bv70iRMmTp+3em/4yx+0NjdW8GCNgbqVx6Hr70He\ncJS9ubrg15iwDZOHaE09m9HiepG5kQuG6U7fdelVaW8D+7EjtYQ+hMweNmzpvT/eX9FK3awz\n+7nOt+KB3NP+pxsnZ/ln95/KBi7Tua5K9YuL47yNtBx9HxSIaxjoDRT69Try0Dxj0/UJv+tX\nyr4xV3eY6+4rib+phqPHjhwi/PHYHD19jwdF7TlVhBBiVXSEmMRLCQBgwtnmtn/fYwgA0G/F\n05qSs2Or/tfyaXvH5tGqCwsebzDgB4BeM28XM2zn12ELAACjvd+abis6agsAoL3Id3p/ngaf\nDEJo6JJbmW05n8Ib06UAgGfw0sisiprg4neaiQIA2exAWk29u7NFAcAi+FdNwc9rUyUBQMTc\n93lNWeX3O8vUuAEAgDT58p+PndjDOrPkhqsYANvQbSkNitN9h7EDCEwOL2x8FsJ6XpEZ5VVl\nv1NDHSgAwDPqWEHtrgWXJ4sDgKjl7pc1O9NyH3hpkas7uQ3BIYQQC8MRO8SyRMXF2QAgN7fx\nsI3ivH1rdYVrrvUJDPXyXzCAgC9Hd53Ja+sx8vLyAADi93kEf1OeFxL7/vuvgvTE6zvs5Tjz\nn/iOcdib0uqmssN8j2cCyM89tNVMoub2U4HBSwLXGnJCcdSOgJfN7XjKLywL2LU89i9Wr5kA\nxyZusmnPzD5tPZ3mdbPO5DafP1MRaE8OHIivG+ujvzp4ILYSZKe52/I2rE4y8gndaNaresow\nZ5/Jm+drAJRE33lUM1D6/dSe09nAMXTF/gWqNTsTIvrrds/GWzoQQj0KJnaIddHpdAAgiEbT\ntZQmTtZq8B+XUHGapArw+170o7Y+II9GowEAVFQIOgZF7p2mqyDOJ0BRtlx64foGTQ4ovP+f\n771WXkSkPbwXUwGgMmW6ZsNFRfq4uJgCQHJ09BeGO1ZW7agzeXK/BuWchlMm9G7j6bSgW3Um\nAKHqNs+QAz4d8b9RVl1UHuUf+B5Afbb7sMbLtqjZ2VEbFPQdNIgH4OfXr9UXs2s6edKkhnkc\nx7BJDh2YPiOEENNhYodYVk52Nh0AREREGpbLyTUZZKFSqQTAr4yMtk775+fnBwAAkQmzxgrW\nKyeUZs8yAYCs6Oi3rWvpx5cvxQDQt2+T4Pj69ZMEgC9fGCd2PzIyigG45OR6Nd7S+EQT90+2\naWDW0VaPgXWvzgQAkHVeYM8P2af2n60aOvx5Yf+JTOAynevav3FVtj59KI2KBAUFAKCsrDor\n/PHlSwkAF5Uq03hfKpXa+pgQQojl4XIniFVVPnv2AgA4VFQafZE3HnSqwnA86o+E5eSEAPIZ\nfL0LUqnCAD+ysrIABrWipWZGxOo2/UErQs99dfPq1fqXUvspb2xFZADdrjMBAIDffr6z7Lm9\n1/2DU5yWymUc3X+5CIQmuk+SbFKTYGNrXawMTqntp4kQQqwMR+wQiyo4HxLxC4Bdd4RJo5XX\nUlJSG1dOS0sDAH4ZGf62HkZDczAbAOTk5DTaUJ6d/RPqRqH+SIRC4QGgf/zYZBCtKCXlOwD0\n6tVkSA4AAIR79eIB+J2S8rXxltTU1AavjQ/kNJwim7xFvXXBdbfOrMJuOM9NlaDFHTjwnPbm\n4IH7lUBxnmtHbmtUAADCMjI8AL9TU7813lJ1tggh1FNgYodYEe3rudlLzv0CEJu0bFrjq2dJ\np8ISGszVor85cfIlAKeh8bA2j76IjhpjyA6QHnnzbYNhtcLIm7GVANxDhii3riE2PSMDDoDE\n0JCEygYb0kOCbwOAvLEx48SOXc9InwMgLiysYUpYERN6ukNyjm7YmTUUZ84354bkI7s9dwX+\nDwi12W567XsqGrue4TB2gEenTqY2KK+MCzvT+ls6EEKoG+j6G3ERqsJwhY6Knx9vH1pkIMkG\nABz9ZlzPrr+xZm0Lfl2fuB81hT+fbjISAABpl1tFDI/T0goddDq96LYbBQAEdLzufKusKipO\nOjZJng2AoM6PKWv1+RTecJYCAJ4hK+7mVNYc+5W/lTj8YbmTupU4XtWuxJFzb4VG1ZIhf7Hc\nSTfuzBrFV5xrZgVyjjjYdMWUs2MBgH1CeOPyB3MlAcAooPaU8yMcRQFAbOS+1zVnRsuLXTuU\nt7qT2xwZQgixJEzsENNU5SKSKqZVjPWGqitJ81YPInNRrX1uf61ouEfVt7il+1xFDnaRQWbj\np0xxMFcR4wAAbuUlt/Ma1H2y1Uy7ypC+ggAA/NTB1QWG3jENqhY+WqfDBwBsfLJqRhYjdJTE\nSQAAInpbnjLObpqTf3+1Jj8AEALyBvaOk8aNUBXnBABO+Sln0mm1tZokdnR69nV3JS4A4JRQ\nt5gwxWns8P5CbJwD588xbWNi15M6sxotwUMeAAAEHSMKm25udWJHp2ddmSXPCQBckhqWjlOn\njDMdKMzOpbzIzRQA+Ke3JzaEEGI9mNghpvFq8PAAdi5eIfFe8oNNRs9YsevCi+xyBnvUfIvT\ncmP3uVmoUoR4uHiEe2vZLT36Ir9x3cjZ9W/MbIBBqlSWcm2bq4UqRZjMyUkWpWpau+2M+tz2\n8SU6vfjjta0zrTT6iJI5ObkFpQcaTVwd+uIHrX4VBokdnU7Lexa00EZDVoibi0dIVs1qbkBc\nXvlJuzYmdj2sM+l0Op1Oi5ojDgC9Fz6oYLC1DYkdnU7LeXJo/kh1iiA3F49wbw3rhYef5qfs\n0AIAueXtDQ8hhFgLQW/NDXsIsYRz44jx59knhFecsmd2KN1fN+nM37dn9jYL/K666e3LVUp/\nrt5WOcft+ky9RBt/uuSMQ8e3jhBCXQ5vnkAIsSzaB//1x7OA13rJrL/P6jLfJWbXf3osLTd+\nr/PyS8UgNmm6zV+3jhBCLAHXsUMIsZ63oQt23sn9Gn/j5qsyLvW1m51E/77NGG9Vx5vyWloD\nqb1E2AsyPr568uTTTzpJaU7INqt2LaKCEEKsBxM7hP6kNPtjam55SzU4Ran9xLm7Kp5urZWd\n+SXmWFDwT5IQRX30gv/2rFRu3yonDWlMWu1SEvXg+aMbD/OLKklCMgpm0+xdly1yUBbogNYR\nQogl4Bw7hP4kbhlFdyfj54FV67X0UcYOna6Kp1vDzkQIoc6EI3YI/YnitENndYpbqkFWUuyq\nYLo77EyEEOpMOGKHEEIIIdRD4F2xCCGEEEI9BCZ2CCGEEEI9BCZ2CCGEEEI9BCZ2CCGEEEI9\nBCZ2CCGEEEI9BCZ2CCGEEEI9BCZ2CCGEEEI9BC5Q3NNU/v5znS5DdMSDoDoQG73FZ1l1rUo6\nJ7NDqFOcx+wI6uEXZaG3CQCAVsHsCOrh4mF2BAghloYjdgghhBBCPQQmdoiBh0spfZbGMDuK\najFLKL2XsE4wVMqSh8yOog5LvVOP1lD6r2GVYBBC6N+EiR2qlZP2uahpadHntJyujwVy0tIY\nBZPGUsF8ZkYwwGrvVHoGg2CKM9Jyuz6Wf1JpqD1Rg4ObX0Sq3+DhY+duOZWQXfmXLSdtVCcI\n+1PNXYjOjdm31GW0sVpvAU6CIGxCCv/ycAihDoGJHapGTzxkP3iAldeZpNrfz4VJZ73MB2nY\nHkzs6gcK0xMP2asPsPRsGIyn+UA1pgQTOEpDxcLzXL1g3p3xHNlf3f5AlwcDVZ2jweidUmdG\n5/zv0ATjAfYbz7yvze6Kki5sNNc0sg36Hz6Hustwm6+/fPny5fBTQXt93Cxk8674TNQaoL/m\nbmfOnfx2+3BIdDqnopWFGrkTD4MQahuCTsdfvj3K39w8UZZ+e/8GT987ZA3JF7Ggp5YZ/8t4\nyca188z7tHO+9t/cPFH2+fZ+H8+dd8gaEi9iQU8tK77QeMlG73nm1PZPHm/3zRNln+/4+6zZ\ncZc8WOLlQximnpXwy3jhf97uFu3tGfi7myfK0m/v92nyTnm3/536m5snyr7cPrzdc88Dspr4\nizjQU/0e/0t/iffyeaay7QwGb55oSZObJ0pD7XmmRM24XhhoWVdY8j54krFLRPGosOSLE8Xa\nfJDy4hIg83zcqD5gDfVkeYQjw7vsaDQaGxsbAETPEzPx1wn+dcWZr81HQgh1NByxQ3VIsqaL\nD8VGe4u8iM/Pj48XWvsgNmh5u3OFvw2mt+niwNh762qC8X4QG7z8b7K6vwtm+JLA+w+8hZ/H\n5+fHJwh53407svRvsrq/jUfWdPHh2Oj6nXOEee9UL9N5frE3V4i8eplf8DJe0OPBnT3L253V\noQ7Bozj9iO9YvoJL2w+9B4DS6zPECLEZ10vr10nfY8hBKG/4H0DNVdfDCSHzLVRkBEjcGhuT\nmrRZ+HzPSBkOMUPvh1V/BlRldS34eNHTxUpTXlqIh4tbiKJq5R4YX9BB54cQahYmdqhO4fsI\nn4mqBpvKdHWEhXX0yzcP03Bcf/E9c6bOFL6L8Jmgqv9fTTCbhqk7rL/4jknBvL+03nHwsP9+\nD9MRFtYZVv6foeqEDRFM6hmoeqccVQ3qdY7GBKa9U0UfIza7qpr5lmlrCQtp6ZfvGqbruv7K\nR5xxxWTCtvZG7PDi/v2fANyWC2cp5Z7cd7JuZJaeeGD/A/bhc2cNrC265zEugMtpf2Tix7fn\nZvRu0Bjty9VFBobLPhgfeRS5Xk+kdRGkJ30UNHHfdODM1evnD3la0q7OMRl9KK1DTg4h1Cxc\nx47JVFRUysvL+fj+9hIGQRCbNm0aMWJEu1ugJ64fNjxUYbFfbLD1Fy9KHCy89K6JK5sAACAA\nSURBVN/2a76Ll+jpvLqTuEaF+MsI2xqMrlGowhK/R0etMzwpcbDw8qbt13YsXqyr8+pe1wez\nQds4THHJzschIzM8qY9g/pVNW6/uXLpIV/9V9PO1XRsMVL1TJqEKi/1iQ+q9UzsXLxmm8+pu\nl3fO/9ab2IXKu/nd9bf+spHyBBaeXb39pv/iFZY6ry8mrhzY1Z2D6vBSqWJA//o1E0CAUHWf\nZ7R9wb6gj9OX9wMA+B21L/CdwLjNUyTrdijTXX1x5xSp2tffqv8tfhUw2Xp+dG+PG5H/DRdr\n/VtqvOK0ce0LU+uxKkWyhn5Br2b5qP7VeSGEWoSJHZPl5eXp6OgMHTr0L9thY2NTUlL6mxYI\nlYWRb1ZKSpAA4EtVETd1pGe4qWtWiURXfz0TKguj3q6UlCQBQEZtMKvDTWdmlUh2fTDz7/zP\no2Ewfay9zpm5MiEYqH2nJBu+U17hpsyIhxi48ErsSgnxesGQqBZLwo2nZJWKY1bHXA1mUFOc\nF45ZPSZg/6OlO3XZoOCM/4nvvWfMG1X/T0o1CwupJo3kRHkYz9r73fLgw2MzBnK36fiV3+7s\n8dkZFpmQnFVQWk6j0yt/A+3tWzqo4v8MhDoPJnZMxsvLa2lpOXPmTGYHAgBCkhLVP7GTeHmh\n+sYHkoQkiSnB1IwkNAhGEoNhtXiEJMRrguHiJdcGI86szkE1ClNTc4HQkKlO1vjsFrpQ9YL3\nXd2ga5sT4n+lWHPjXN0GtzdJSko2bSXp4vG8Ivk5bvZtzOqgLMbDyNyvzGqNT5CZsqwILyfb\n54DRFntKSsoA2tgUQqgNMLFDDOhsevc/ZsdQS3fzu7fMjqGW7uY375gdQ30s9U4NXfMugdkx\noFo/Lkfcq4TBxkYC1QVsw+bN1drtte/Ezl6f9sdxmAe7KraiGf0d0aMiLGdaG8H5KH8rqdaP\ntcUeD/nAOyniwjq7mtu/M8uyAfq19TwQQm2DN08ghFBPU/o+ePrSC0XCYzxmKtSV9nVdYMMZ\nuWfS0qD3oo7zHFu3DApJyeXsg5NjSgPtDaad+9z6RY/pdDrwi4rWLupTevv0JVy0GqHOhyN2\nCCHU3VWmP7lypQLoFaW/ctISY66EnYnO4B3mHRHkIFq/mtCEhVM9TAOiQW7FvJGtvx7KQXU4\n9oCXb8Q4R4OiI1EnpypwAQDA9/hL91N+A7z5+Bsg81nEOT5uAEktOwMqJwBo2dhIHj6x0dcx\n2E2d+2tsyCLXc6X8HXrSCCFGMLFDCKHurvSWt+0tADYusoCQZJ+BGjZrT7m6jtMQa7xEONfw\nCfbiAYf7urtpte1yDZu09YF71wUsbJ0N7QpvXXBX4QF4FTB1fFDNynTx/lPG+wOA6eEfUa5C\nACAwas9V/6WLfW3lVxWRZJSHT913TtvbeE0HnCxCqCX45AkmU1RUXL58eQfePPE3T57ocH/z\n5InO0O4nT3SGv3nyRIf7mydPdDh88kRLmjx5ok3KY5fI6x0cHJoRPlm4oyJCCLEUHLFDCKGe\nL+d93Lu0pKPL9qf3dTvtgFkdQj0WJnYIIdTjVdzw0J1yhSylbLv79AYdFhosRgh1MEzseprU\nZ8yOoJ7ifGZH0FA/VvpCy3rP7AjqkVP+wewQ6ryPYa3xpPQkFvpvYzqnfftxOEXQnTo2FIQQ\nS8LlThADz3ZT9HbHMDsKVhTrSVHwxJ5BCCHEojCxQ7VyvmQWNS0tyUxjocEc5sj5nM6gZ4rS\n03BZLsQiCt9f2e5up6skI8zLxcUjKK2obTNjbfCDLy3fTJW5z5ggzAJrRtaTNqoThP2p5u4V\nyY3Zt9RltLFabwFOgiBsQgo79AwQQh0DEztUjZ58aPaUAc4BZz6W1BSVJF0LMB/hZBuW/E/f\nOk1/c2i8/oBRPmfe12Z3RUnnfcw19GwD3/zTPYNYAy3l9LTBararI7LlRy/Zdij0RPBur6lD\nORMCZhpqe8a1tCenqNygQXIirbx7/dvtwyHR6ZyKVhZq5I6IGyHUGXCOHapGyHteCNUODfKc\nMjlgkEhRCWyZPCm+SHPJ5uPzDKT/6Wd2E4M87z/UPrjV02pYgLp4URFssdSNL9Rfsj9mnlnv\nf7pnECugJW4ePfXYtyHrHl7z1hKoLXaet3pr0infJ82kYOXFJUDmEZ0Y/Hpiq480cM3zXG82\nAIied/5c/F+GjRDqJDhih+pwSZq6eMaeminyJin/Z1K8gOuD86uXG0j/1bpZPQOJYrpgb2zk\nKpGXL/ILXsQLrXwQvX+5WW/sGcR0ZZe2bn9ZruZ5pH5WV4Xc33H1VNXqF1WXWQ8nhMy3UJER\nIHFrbExqcim2kcLne0bKcIgZej+sWuaQjQ2/MBBiffg5RXWKP0fsWa06PrhssLKwoLJ+Rciw\nkV7rIz/jTBooTI7YNF11+I4ynSHCQkP0y3cOG+q8/nIy9gxiuieRkQUwaPQYxdZUvucxLoDL\naX9k4se352b0bqkm7cvVRQaGyz4YH3kUuV5PpGNiRQh1AbwU2508f/785MmT8vLyDLfa2NjI\nyMi0u3F68vox7qFyE/3Or7XODKA8h4WH3bbfPbF4o6tO0v7E+fL/7jVH+pv1RtahCvP87h2w\n/rKe8hgWnvfefmPvYg8znddXE1cN+nd7BjHf78+fvwMMpVLriujlJUVlldUv2LjIZK7aP+DL\ndFdf3DlFqrZqCTBU/CpgsvX86N4eNyL/Gy6G/8ER6lYwsetO/P39T5w4wTB7Y2dnl5WV/ZvE\njpBfGHpqpZgICQAyq4q4qCbTw/XsskpF/ulf7cSghdefrpQQJwHAl6oiEtVyWbjJtKxS8X+6\nZxDzMbh7J8t/hPTih9Uv+ix9lLpDp2aTmoWFVNMdGsqJ8jCetfe75cGHx2YM5O6wQBFCXQQT\nu+5EUVFRVVX18ePHndO8kFjNBRd2Tl4yVN8pxyUiydU5x+s+hCTEq39iJ/Hy1vQMSVySxLSQ\nEAIAAFLv3hIAqampAErVRaIOAQ+0CgAKLs632dFwrSJJSck/tph08XhekfwcN3vM6hDqlnCO\nHWJAw/1dpLsus6NgRdre7154Y88g1jHU3FwQ3kSE1z3IhFNGRV9fX19fu59gexrU3xEdOKrw\noLWR+/VMXM0Hoe4HEzuEEOq+SLYey9U4X2xy8Xn2s4NaVHI5++DkmNJAe4Np5z5X/nkHhBAr\nwUuxCCHUjbGprAo/+t7C2Vuv/w2HaWONVHoLsZfmZ358cu3EM+BWlmrPsB0H1eHYA16+EeMc\nDYqORJ2cqlA1HeN7/KX7Kb8B3nz8DZD5LOIcHzeApJadAZWFnqaL0L8OEzuEEOrW2OQcjyYM\nHrd/1+EL57df8sstpvOI9FJQ13Pwi54z1Ui2nY1KWx+4d13AwtbZ0K7w1gV3FR6AVwFTxwcV\nVFeI958y3h8ATA//iHIV6qhzQQj9LUzsEEKo2+NTtPUIsPVovkL/1S/oqxsXSs2Lps9rvo6o\n8bZnv7bVvTYLzKcHdkCwCKFOhHPsEEIIIYR6CEzsEEIIIYR6CLwU29PwsdLDf/hEmR1BQ1/e\nMDuCerhYaZUwOlmY2SHU4Wn8zFMmk2H8qBeEEGJFOGKHEEIIIdRDYGKHGHi8maKxOYbZUVR7\nvImisYlVgkEIIYRYGSZ2qFZOxteipqXFX9Pyuj4W1goGIdZVGmpP1ODg5heR6jd4+Ni5W04l\nZOPawgj9izCxQ9Xo7w5NHTXAceeZ5OKaouKkSzvN9Wxtj77r6icL0d8dmmrLKBgbJgSDEMvj\nNl9/+fLly+Gngvb6uFnI5l3xmag1QH/NXfw7CKF/Dt48wXI+fvz47ds3Hh6epps+f/5cUlLS\nSccllDxvXNY+ss9zrE2AilhRMWwZYx1fqL3E99I8k15EJx20pWCuaB/Z6znWumEwl5kQDEIs\nj112qI2NZc2rWcvWegVPMnbZOHr6wOSLE8WYGRlCqIvhiB3LsbCwMDAw0GLE398/KSmp8w7N\nJW0657/YiwtEXr/OL3gdLzj/wbUty016MUgxuwCXtOmcTbEXF7JEMAh1LzyK04/4juUruLT9\n0PuqEnpm9HaX4QMpomQSj6BEHxWjcb6xpbX1yz5d3TDNZKCMIDeJLEoZZDxpe0zVEyY+XvR0\nsdKUlxbi4eIWoqhauQfGF9TulbRRnSDsQ1OurrbXkOHn4RUfYLniUgYNSv4XusB8kCQfrwhV\na+KORz+69NQR+tdhYsdylJWV3dzc8hhZt26durp65x26KCVixyJVm4AyLXVhQXX98gPDTBau\nv55S2HlH/EMwC1Vt9tcEEzDMZAHTgkGo2xG2tTdihxf37/8EAEj3dxy56jaPw8aQK5E3zhzc\nNFOPJz+vvKpmxbv9Vlo2PlFslqv2n70cHrhlti49pfqjlp70UdDEfdOBM1evnz/kaUm7Osdk\n9KG0+sd5uc52yf9U3HcfP759suiTbWPHLV03wWZbgcny/aFHvIzKLi63nh/xs4vPHaF/GV6K\nZTkEQZBIJGFhBuuK8fDw0Gg0NjY2Op3BPLPQ0NDJkye3+7j0d+utnEL7ufhd32r91ZcSDwtD\nl2yPOrJ4jYPO/0ITlyp16QVQ+rv1VpND+7n4Xd9m/XUnJR4Whi7dHhW0eM14nf+d6OpgEOqW\neKlUMaB//ZoJIEBPeBhbouLtu85ZqWqjxeja3xX5Jz087v42O/zqliuFqN7oVLPReMVp49oW\nTa3HqhTJGvoFvZrlo1pTmNln7rsLbr0BAOx1iuNkl/vtmxyefNReCABgVO/Pd4f5h14LsXfE\nLxuEugZ+1roZOp1Op9NPnjypoKDQaNOgQYP+pmVCaeH5GyvFRUkA8LWqiEQ1cws3dMgqEe36\nOXYLz99sEox7uOEEJgSDUPdU7w9AQm3oENLpPS7unHPshhvoalAF2Gs20e5fv1XEPcbdhcLo\nk1X57c4en51hkQnJWQWl5TQ6vfI30N6+pYNqTW3N0aN719SmqKgIQbzJaBuh6gI2VdVBUJmW\n9gWgT6ecI0KoMUzsuqWBAweqqqr+uV7bCInXPCiCnZOXDNW/+LlEJbk6+khtC4aL6cEg1A0V\npqbmAqEhIwUAQF0QfpvTZ2vIXreDK4rYhOQNJyzZutlNSxjgV3Z2KchQKIzm5ZTFeBiZ+5VZ\nrfEJMlOWFeHlZPscMNpiT0lJGUDNk1PExOrdnEEikUBQVJSjQQF03j1fCKEmMLFDDGgte/eQ\n2THUYqlgEOouflyOuFcJg42Nqp7Qxi6hN2/fpXn7Kn+mJtyJ2OO1yt2iUDo91J7MLy7ODTEZ\nGTQY0iS3iz0e8oF3UsSFdXac1SWZZdkA/bryPBBCbYM3T3QuHh4eQUFBkeYlJyffuHGD2WEi\nhHqU0vfB05deKBIe4zGz0ZwNdgHqEPtF+xboQ15CQioAsBlamfOWXtx/JKNpM3Q6HfhFRWuy\nOii9ffpSbudGjhD6Szhi17l+//69fPlyFRWV5irMnTtXT0+vK0NCCPU4lelPrlypAHpF6a+c\ntMSYK2FnojN4h3lHBDlUTWnICnSwvUl1tB6q1FuCtyz90ZEd94k+c0wVAACEJm7bFqw7103b\n7O1KF5P+4rScD0+uvum/1d+pl5aNjeThExt9HYPd1Lm/xoYscj1Xys/UE0UI/Qkmdp2LIAgj\nIyNTU9PmKnh5efHz429KhNDfKL3lbXsLgI2LLCAk2Weghs3aU66u4zTEam6R4FM10rh2Onhd\nSFpmAY1Pgqpq4XNtzRKjqqE4DiX3a08oW7y3h22YtTefzi9JVTNyseIHAIFRe676L13sayu/\nqogkozx86r5z2t7Ga5h2mgihP8PEDiGEujFupwi6058q8Q6de/DC3BYakR+17sSodU03CGm6\nB913r19iTV9d82P/1S/qXgAAgPG+TPq++gUcrYkOIdSBcI4dQgghhFAPgSN2PU1mMrMjqIed\nxf5/8bDSRe/8TGZHUA+pE59U12a8on+u05W+pzI7AoQQajUcsUMIIYQQ6iEwsUMIIYQQ6iEw\nsUMIoW6sNNSeIAiCEHW9UdZgA/3JEjmCIAjCeF9ORx+04nmg6xhjVTkpYTKJLCKrpDN21bGE\nvI4+CkKoHTCx605ev36dkJAAAB8+fGB2LAgh1sHDz19wJvhScb2i8ttHQlM7azGlys+v31T0\nGzlz5Zb9h/f6zDYhPdkxTddk7dOKTjkaQqgNWGxyO2rR9u3b9fT05syZo6Cg8OfaCKF/hYC9\ng9aZ0OBzP8ZPFa4qKbl85FSe/oSp2YHB7WqxvLgEyDyczWwl2fk9sqt7OcPNXkxV5b8DwbE+\nQwzbdTiEUEfBEbvuRFJScvz48cyOAiHEckTGu4zivBUc9rX6df75I+ElFi5OMg2r5T096G6p\n0kuQm4ss0nfoOK8L72sv3yZtVCcI+8MJIfMtVGQESNwaG5MAyj5d3TDNZKCMIDeJLEoZZDxp\ne0wBo8Ozy8rKAHBw4FABQkyHiR1CCHV/vLbTHYTvBR9LAQCAb2FHbnCMcnFosHJM6VNvE4M5\nxzLUF+4/e/HEtgkicVvH6o4NTqtX5Z7HuAAup/2RiR/fnpsh826/lZaNTxSb5ar9Zy+HB26Z\nrUtPSSmsq11ZVlRY+DMnPfHmLpfNdwSNVszR6YpTRQi1BP++6q6cnJwyMzNFRESqXrKxsS1b\ntkxLS4u5USGEmITTfPpkGYPgkMSV61VSjh6JFna4assLz+sqZB/13PKKe8yZ+8fHiwAAWNnp\n82opr1n5350ph4ZXfxWU6a6+uHOKFAAA5B+387j72+zwq1uuFAIAACxGN3yIxPXZkrZHiwAA\nOGVtfaPCFg7EoQKEmA4/ht1VXFzcr1+/hGsICgpycjY3HwYh1POx67tMVXx/NDiWlhgcHC/j\n5GLOVX9zZcyd+7957ZzHidSUsPV3cR4G3+/ceV1bSc3CQqr6R9r967eKuO3cXaqzOgb0vCIf\nPLh7/XyQzwTRB4vMLTc/LWuuKkKoq+CIXXclLi5uZ2e3cuVKZgeCEGIRqtOdB2/eFbShLOq9\n4rRzeuwNNv7Kzf0NUtLS9dM0KRkZAhJzc2sLJCUla+tnZ5eCDIXSwl//wgq6+goAYGw5Zrw6\nm+KoNcuOON9zk+6o00EItQeO2CGEUA+hMHW6Xl6Iz4HPmtOdVRpt4xcV5YKsb9/o9coyv36l\ng6gow2e48YuLc8PXjAxaq47Mr609ACrfv//UzsgRQh0FEzuEEOopek32WD7K1nbhqmlNVkRi\n1zc14iq8fOxCfk0J/X3IsViQGD5cmVFTbIZW5rylF/cfyWi6jV5Z2TDfo3+5dCUBCHn5vn99\nCgihv4OXYhFCqMcQHrU5fBTjTeJT/1vpb+DjbDTtk8d4Fd6s+4fWbYsXtD7iNZzx94DQxG3b\ngnXnummbvV3pYtJfnJbz4cnVN/23+jv1Kggco3ZCYLy5er9e4qSS7x8enQs5/bhkwOINzngd\nFiFmw8QOIYT+CdxD1t+9L+21xn+X26nscnIv5eEe5zZ7j+3TXH0OJfdrTyhbvLeHbZi1N5/O\nL0lVM3Kx4gcA8lB7uzvHIoNuBWbmFRF8knKqRsuOrvCYosHbhaeDEGIIEzuEEOrGuJ0i6E7N\nbVTemETfWO+1yNA5ATfnBDCq2n/1C/rqJo3Lj1p3YtS6xsVcGtP3nJ7enmgRQp0N59ghhBBC\nCPUQmNh1MzQaDQAMDAweP3587do1ZoeDEEIIIRaCl2K7GTExsYCAABERkRUrVgwbNqxpBXrr\nFifoGjwCzI6goZKfzI6gHg4SsyOoR6TZeVZM8PUNsyNoKP87syNACKFWwxG77mfOnDkODg5S\nUlJCQkLMjgWhOg89KHIeMcyOAiGE/mmY2CGE/kbO589FTUuLPqfldH0s/6TSUHuC4HO9Uf0y\nPzZw3brQF7877gC5MfuWuow2VustwEkQhE1IYcc1jRDqeJjYIYTaj/760JihA6zXnnlXm90V\nJZ1ba64yxPbwa3pLe6LOkR8buH59hyZ2324fDolO51S0slAjd1yrCKFOgnPsEELtRyh7Pnyq\nfWCTp7lWgIZEUTFsGaEZX2i45OCTeSP6NPvweNSdDFzzPNebDQCi550/F8/saBBCf4Ajdgih\nv0KSNV0YEHt3tciLhPz8hHghrwcPDi0f0YeH2XH9i+KWUeWWPwa4OZ2fIAiCINS3JAMA0DOj\nt7sMH0gRJZN4BCX6qBiN840trdolaaM6QdgfSQxbbKUizcfNL6VoMH1ffH69RtnY8HsCoW4E\nP7AIob9S+CFio5Oq4ZYy3aHCwkP1y7cN05y8/tIHnInFBBpeMQ881QEMt79JSUlJSUm55kYF\ngHR/x5GrbvM4bAy5EnnjzMFNM/V48vPK6+13f7nDYQHX4NjklPhjzpyX51vNv4jvH0LdFF6K\n7a7KysqSk5OjoqKqXhIEoaOjw8uLT/RBXYr+er3+iFCFhX4PA60z1lLiYGGEz/brfouXGuok\nRiZ6KePV2C5FEqZQhEkAPGK9qVS+mlJ6wsPYEhVv33XOSlUFFqMnN9yPZuZzYf1YYQAAKc9d\nbsfVtxy/EWw3Dr8fEOqG8IPbXWVnZwcFBQUFBVW9JAjixIkTEydOZG5U6F9DKC+89XKlhAQJ\nADKqiripVivDh7tklUhgVscaCLWhQ0in97i4c86xG26gq0EVYG9UQ2P4cOHaF4qKilCRlvYF\ngJVWN0QItRJeiu2u0tPT6fXQaDTM6hAzCFVldQDATuLlJVWnDCQJSVxlkWVQF4Tf3jNe9Mle\nt5FD5ETFFEznBDz7Ub+CoKBg3QtOTk6AkpKSro4SIdQhMLFDCHUMnQ3vXm/QZXYUiAF2Cb15\n+y49Sy/4kfLkrLdO5lF3i/kRxcyOCiHUGTCxQwihnoNEIjU/3sYuQB1iv2jfAn3IS0hI7drA\nEEJdA+fYIYRQzyGloiIOIWG+5wfa9eHlIFNUBkrlBzrY3qQ6Wg9V6i3BW5b+6MiO+0SfOaYK\nrW3ye/yl+ym/Ad58/A2Q+SziHB83gKSWnQGVszPPBCHULpjYIYRQz0EYewWv+LQiZPqIbb/K\naWqbP7xYKa1qpHHtdPC6kLTMAhqfBFXVwufamiVGrc7KXgVMHR9UUP0i3n/KeH8AMD38I8oV\n51EixHowsUMIoW6M2ymC7lS/QNp6yzXrLfVLhs49eGFuM7v3X/2CvrpBCYfjObpj/QKzwHx6\nYEeEihDqApjYMRmNRsvOzv706VNtSWFhIY1GY2JICCGEEOqmMLFjsszMTC8vLy8vr/qFycnJ\nu3fvZlZICCGEEOqmMLFjstevX1dUVNR/GOPMmTP79+/f7gYl5DoirA5CFv5zna4Uf4XZEdSj\n7/TnOl0mjZWe7S5GZXYECCHUbWFix2RUKrVRiYCAABcXFzNiQQghhFD3huvYIQaebKVobo1h\ndhTV4tZRBq5jlWAQQgghVoaJHaqVk/G1qGlp8de0vK6PBXLSMxgFk5GW2/WxIMTCSkPtiToc\nvGK9BxhM8jn/tvbzU/E80HWMsaqclDCZRBaRVdIZu+pYQgd+qDP3GROEWWB+9cv82MB160Jf\n/G5Y6dlKKtGI2LzojgsCIVQDL8WiavT3h5ynHZCYsMNnlkN1UXHS5UML1p/KnHLs5ULFLn2g\nO/3toYljDkhO3bFlQU0wRUnhexasPpo5PfzlsgH4dHmE6uM2X392/mAAenlhVlLUwR3e4268\nDEs6P1ECACo/v35T0W/kTHs5GRGOws9Pzx7cMU33WnJMvM+QzvgCyI8NXL9eiLrMSb3xjBI2\nA4/TC4bUviTJD+qEwyP0z8PEDlUjFD2vXdAOCfAcPzpARbSoGLaMs48vGrJkx4V5xjJdnUgR\nAzxvR2kH+nramgaoiRUVwxbb4fGFw5bsiZpnSsGsDqFG2GWH2thYVr9wHCeVLuYScfJG6cSp\n3AAkO79HdnVVZ7jZi6mq/HcgONZniGGXBkn01h03zr5LD4nQPwgvxaI6XNKms3xiI+aKvH6T\n//NNvKD7g8v/LTeW4WFKMKRepnN3xl5fKvLqVX7Bq3jBpQ8idy03pTAnGIS6E35RUU4gODkZ\n/+HOLisrA8DBUW8rLePm+nGDZfm5uYX6DJm4KerFngZXV+HjRU8XK015aSEeLm4hiqqVe2B8\nAaOmIW4ZVW75Y4Cb0/mrrreqb0luUKGipLissgNOESHUHEzsUJ2i1AjfpaqjDpZpqQkLqumX\nHxpmtmT9jdRC5gTzMWLrHFWL3WXamsJCmvrlu4fpzV5/9SNzgkGIxVWUFhYWFhYW5md+jAud\n632hTHLyVMv6iV1lWVFh4c+c9MSbu1w23xE0WjFHp2ZT0f1lJtbrosmjt524dMZvVq8ol7G7\n3jdoPT3po6CJ+6YDZ65eP3/I05J2dY7J6ENpDMLQ8Ip54KkOYLj9TUpKSkpKyjU3al0IEc5C\n3GRebpIAVddx47W08g7uA4QQAF6K7Y6ePn1qZGQkLS1dv5AgCD8/Pxsbm3Y3S3+/3sY5tO80\nvyubrL/5UeJh4bFF22+HLF47SedtSOLirp5jt950TKj8HL+o3dZfN1OewMLTq7bfOrB4lY3O\nmwuJHjjHDqEGio6O5j9a+4rUd4z/zYN2DZaRvD5b0vZoEQAAp6ytb1TYwoE1f9ZnHV23N1nc\nNSpqjyk3AIC5jUqFou5uGFi3s/GK08a1L0ytx6oUyRr6Bb2a5aPaKA6SMIUiTALgEetNpfLV\n20DuazbDW9NEjSrKnvcx9tSuPWuso1+cjD/n2OvvTx4hVB8mdt1PeXl5SUnJ4sWL6y93x8bG\nNmTIkBb2+iNCceGZyyvFRUkA8K2qiEQ1nR1uMC6rVLTr59gtvPRgpYQYCQC+1gRjvjDcaHJW\nqRhmdQg1wmOz49YKbQCglealv7i6Z/Nc81G029fnKrPX1NDzinzgWlb4/dPT8L2+i8wti2/e\nXjWEBACVsfceVoi5OFZldQAAnDoTx1F376jXfOW3O3t8doZFJiRnFZSWNTG6cwAAIABJREFU\n0+j0yt9Ae/uWDqqt/TQOnBVY97jZUZMnGU5VsT6+bNujCbt18QONUIfCxK77qZob4+LiQiaT\nO7RhIXHR6p/YuXjJUP2NwCUqyYzlkoUkxOqC4a0JhiQmSWJCMAixODbJQfr6+tUvzEZZi3+V\ncV6+6tTky5OFqguFFXT1FQDA2HLMeHU2xVFrlh1xvucmDfArN/c3SElJ1W9OUlKy3quyGA8j\nc78yqzU+QWbKsiK8nGyfA0Zb7CkpKQPghnYRHuk8Svx4QFxcBujKtq8JhBBjmNghBjQXv3vA\n7BhqDfF895TZMSDUrQipqFDgysuX72Hy0KZb+bW1B8Cxt+8/AUhX32nxMjMToG71kaysLIDa\nK6mxx0M+8E6KuLDOjrO6JLMsG6DfX4VYUVEJUP9higihjoGfKoQQ6mG+P336GUBCQhwA6JWV\ntAYb6V8uXUkAQl6+LwAAsA8z0ufIuXj6TmlNhYonp8+n1t+BTq9K/6qV3j59qfmFwkkkEkBJ\nSUmDQ5aXN7wV9tupgIg86DNsGE6xQ6ij4YgdQgh1d5XpT65cqQAAWumPjJdX9/tFlYmPXuwk\nBwAFgWPUTgiMN1fv10ucVPL9w6NzIacflwxYvMG5+v4ryWnr5u8a7udowbdpqU0/trRbu9eF\nV0rVG07TsrGRPHxio69jsJs699fYkEWu50r5mw1FSkVFHELCfM8PtOvDy0GmqAyUIhUdc1AK\n4plgpalAEeXI//TozMFjcbmyUw95/NW8YIQQI5jYIYRQd1d6y9v2FgAAwSUgJSunPMl3l6f7\nCCkAAPJQe7s7xyKDbgVm5hURfJJyqkbLjq7wmKLBW7Mzr+GOO1cEFnkGLh7vT4gPNHMJCNT3\nNNsgJFR9MVZg1J6r/ksX+9rKryoiySgPn7rvnLa38ZpmQiGMvYJXfFoRMn3Etl/lNLXNH16s\nlOdSMRshEnr94K3D2QVlnEKyA3Xd9q9cM3uYRCd3C0L/IoJOpzM7hp6Mg4Pj5s2bpqamrd9l\n9OjRVCp1165dzVV48uSJtrZ2UVERw5snvia2J85OQhb+c52uFH+F2RHUo+/E7Ajq+ZzA7Ajq\nEaMyO4KGEq4xO4J6TOd0wUE+7zFSXFTik/LEo08XHA0h1KFwxI6l5eTkvH37tlECl5SUxKx4\nEEI90WP/eVHcpkOVZPjKv7+7F7J5231Bx3PTMatDqDvCxI6l2draxsXFMdxEo9EYludmdGZA\nbVT0g9kRNCQo9uc6XaaElTon8xOzI6iHT/TPdVCHIrPnRe1asCstu6CMQ6i3qsnSC/+tHi3O\n7KgQQu2BiR1LU1NTk5GRCay3sicAJCQkmJmZ4ToBCKEOojIn7G5XXONFCHU+TOxYGkEQXFxc\nwsINpqrx8zd/QxpCCCGE/mE46oMQQt1axbeHhxbYDlGiiJBJfGK9+qmbjHfffONLzebMfcYE\nYRaY34qWnq2kEo2IzYtudRzPA13HGKvKSQmTSWQRWSWdsauOJeS154wQQu2HI3YIIdSNfT8/\nbfD4sDLVie4r5qnKcBd+/fS/xzfOH7rksMqyXav/shl4nF5Qt74cSX5QC5UbqPz8+k1Fv5Ez\n7eVkRDgKPz89e3DHNN1ryTHxPkPwmwahLoMfN4QQ6r4+h2wNyxSfdv1hiGXtwnTzV20vKytv\nZ4NEb91x4+zbsyfJzu+RXd3LGW72Yqoq/x0IjvUZYtjOYBBCbYaXYhFCqPvKy8sDkOrXj7dB\nKUEicTW/T9mnqxummQyUEeQmkUUpg4wnbY8paFChoqS4rJLRnh8verpYacpLC/FwcQtRVK3c\nA+MLGNUDAAB2WVkZAA4OHD9AqCthYocQQt1XfwMDcXi1d9bKY/eScn63YoeKd/uttGx8otgs\nV+0/ezk8cMtsXXpKSmHt9soIZyFuMi83SYCq67jxWlqDkb/0pI+CJu6bDpy5ev38IU9L2tU5\nJqMPpTVov7KsqLDwZ0564s1dLpvvCBqtmKPTISeKEGod/FOq+ykrKwMAX19fTk7O+uUODg5y\ncnJMCgohxBTc1jvOb8x23rh1mvFW4BTsrTLM1Mp+qruLsQzj3+75Jz087v42O/zqliuFAAAA\ni9G1D0Eh9zWb4a1pokYVZc/7GHtq15411tEvTsafc6yZrWe84rRxbVOm1mNVimQN/YJezfJR\nrS29PlvS9mgRAACnrK1vVNjCgTh+gFBXwsSu+xESEhITE4uIiKhfyM7OPmTIEEzsEPrniBp4\nXXk398OjWzfvxD55/OD26f+uB+89tPbmg/U6PE0q0+5fv1XEPcbdpTqra2jgrHqLZo6aPMlw\nqor18WXbHk3YrVtVvfLbnT0+O8MiE5KzCkrLaXR65W+gvX1LB9Xa5vS8Ih+4lhV+//Q0fK/v\nInPL4pu3Vw0hdfxpI4QYw8Su+1FRUcnOzmZ2FAgh1sEhpGDgoGDgAACVWVHLLEb6bVx6wOXh\n4iZPBfuVnV0KMhRKq0bRhEc6jxI/HhAXlwG6sgBQFuNhZO5XZrXGJ8hMWVaEl5Ptc8Boiz0l\nJWUA3LU7KejqKwCAseWY8epsiqPWLDvifM9NusNOFSHUMhwjRwihHoRd0mzJNA2gJSa+YbCV\nX1ycG75mZDB+ImETFRWVALWPuYk9HvKBd9KeC+umjdTXVBnYv39/rrKW/sbk19YeAJXv37PS\nA+sQ6vEwsUMIoe4r/+ObL2UNiwri4z8CSElJMajOZmhlzlt6cf8RBg+VppeXN7wV9tupgIg8\n6DNsWPUUOzqdDvyiorVze0tvn76UW7d7ZWXDdJH+5dKVBCDk5fu27ZQQQn8DL8UihFD3lXrY\nbkgQv+2kcWZaStK85flpz68cPnAhV9h866zBjOoLTdy2LVh3rpu22duVLib9xWk5H55cfdN/\nq79Tr6JjDkpBPBOsNBUoohz5nx6dOXgsLld26iGPmuWKtWxsJA+f2OjrGOymzv01NmSR67nS\nugccFgSOUTshMN5cvV8vcVLJ9w+PzoWcflwyYPEGZ7wOi1AXwsQOIYS6r35O27fRIm7ePb4l\n7EvWjzIOoV6KmuP/2+q52JbKeAcOJfdrTyhbvLeHbZi1N5/OL0lVM3L5P3t3HhDT+sYB/Jlq\nmmnflbRaiqiQ/aKVRCtlX9NF2fe1S3Fda+iK6wpF9iwhe9m65YfsruxbFEp1tUzbzO+PtolU\ntJyZfD9/zXnPe97zHJqZZ97lHAcFIpI2teulGnZqy9mtHzNy2cq6Jl29N83zHd+tUcmhis6B\nkUEzpwc4NZ+fxdFuYzNyY3jnxVa+xXtlO7m6RO88t+1scPKnLJa8pqGZ5azQuXNGtJOrOBAA\nqBMsgUDAdAwNmZSU1JkzZ2xtbat/iJubm4GBwbp164jI29s7PT1979691T/83qnvDrLucEXs\nEz3jA9MRCGnemekIhNyLYjoCIc07Vl2nPv17hekIhNhOYDoCABBtmGMHAAAA0EAgsQMAAABo\nIDDHrqHRasF0BEI01JKZDqGcqP0VrRNkSHwk0xEIUVJnOgIhIjX0CQAgXtBjBwAAANBAILED\nURezoJ3OgmtMRwEAACAGkNiBaPr06k3216VZbxJT6j8WABHGC3NllZDiKqhqNWtvM2Diin03\nP5a/23BqzMaZnm5W5nqKbBaL5RiSWVFj/I9X/5riaKGvKsuRUWnSspvb7xc+V3QiYYPDKwsv\nPTZ4yZKw23lVXEXyRisWyy44vYKQHq35hctisZS9zguVnhgtX1EsJv7/Fu0XvIvdvtTbpZuJ\nvrqcrHIT407O03dcT6nm8zYAxBrm2IEoEjzY5eywU2vs4g2znIuLsp4eWLNoZvCH8aejFrWu\n6PnlAD8vbm+/g5Pbk6Ag+78Pr+//E7nHf8jmNRsWHoxcaq1aXCUpamvIRXZ7Cwd7dlh4fIWt\nJB4a1WNwWFrrgeNmebZsLJn+8u6lpKRcIgWhE9ku3DWhbbmjdLtWFll6bLCfn7LBrOFtpX/k\nwvhPAj0Xv1DVoqSccuUdJoUddCwo2xbc3zLW77ymk1Orou3cs8vHBTyz7e82eZSxuiD5ZnjQ\nJs9uETdO3grqpfQjcQCIDyR2IIpYradei20ftPIPm66h7TWys+hP6y53P/cYH/yPp70esjqA\nL0jqdnJ07FOyNW7Wbwt3DLXyXOY2xuRpxJCilTEmvrdSF0sQ0cVJhypM7D7u9vYMy+obfOvg\nWMOSJGzGVycy6O7u3ufL0grlZ+eQrMx3X4owwfPAsQtfDdo178OAqTHl9mh1cHXvULZZcOHC\npM/Ufv7YdsUfD2y7tQ8TjVuU3Elz9PghrWyMff5ascevl7corRQCqH0YigURxdHpMePP41fm\nK9+6/V/67bvK845e3eRjr8dlOi4AMSBjNGZ7wAD5jGOr/35cXCQhUfnH/YvQPyP/az15xVhD\naRLwf2TQMmFZWxbLdevNkMn2ptqKHG67ZQdmGRjO/h/RmTEKRUOlbVc8LaorSIpaPqiDngKX\nq6RrMdD/TFIFJxQ8D/Ja+Mg5aE1fxSrOnHM8eM97qZ5eo41KSiR1yrI6IiKWnq11C+K/fSu8\nUD/3eaTfCEtjTQUOR7aRsZXXhn9SCUDsIbETY3l5eR8/fkwr0cAeIpL59LTfaJtua/K6dVRS\n6dgpf62T2ai1R59mMR0XgHhQcXK1lKTbly//V63qOVcu3xBo/aL/cE7fVuocKSlp1WaWY9bH\npnz5qZKXlV5eVl65KpfmuG+WHr7p3L1nD8PH9loYc2VBW6Keqx+8ePHixYsXJ70NiIhy4ubb\nOiw8I9H3j7CIAxu8NM+M7r/u8RcnErza4jX/jsOGDS6qVIW08ODD6bJ9vYZW8lDaDzExT0jO\n3LxZSUHh07+dOjquiFVyX7rjaMTuZS7SJ2fa2Pper2o2IICow1CsGLO0tLx69WrpZmho6MiR\nIxmMpxYJHqzt3PeQ0ST//22xS/RrF0e/nlj8W2Tgb9Ns+909eeE3zLEDqJKcgYE6Cd69Syaq\nqseLiN6/e1dIn/dNHtW438LAiA4qadd3+vlPt7n1Ke66fzt2abWsXe4qu8odaLs17byXculm\nbtdFEWtHlN0wMluFQySjrmdgIF9a9jHUN+Ch0rDj0X85yhMR2TsY8ZrZBZOJULNvtvw651bP\nDf8ObkTEqzz0t7u3neEpD/Ny/+bsOcGb0F/nnxO0W76of8nY8H8H5s46V+gQeuXYSG0iIurj\n1F7SrNPq3/ZOOzVKrfITAog0JHYi5/79+0ePHl2/fn3RppraNz9jWrVqpampGRAQULSpp6dX\nH/HVC1brX6NvTNbUkCaixKIijm6/2TvsRn/M0UBWB1Ad39WJz+fzibJyTNed2jPNkIjIzqGT\n9KtWs9asjJi/z710qhy378pTszsJH6hiLC+8aW5vX9VtwAtjLlzJVxk5wrH0QBnbUQObBG8o\nq/ImeNycuI5rH4yppA+uxNMd2y4Xant79f3WfL6UM1Mcxh2XdAsJn2sqWVzGvxx5+rOsi9cQ\n7dJqUh3cHHVWbLz0PxrVt+qzAogsJHYi59ChQ8+fP5eXlyeiNWvWSEpKfqumlJSUvLx806ZN\n6zG6eqOoqVH8SlJaVq5kzgBHQ4PDWEgAYiXz5ctUYrXTrt7jVop+Qhr16WNYWtS8r4PRrLib\nNx+Se/uSMsnGZlZWVpW0o6mpWdWpPqem5lETHR3hMh3hzZR9k2dFtZwb666Ynp5ORLnZBUSC\nvKz09HRpOWVZtvCBghvB228LjBd49ajwk1Lw8dQU2/5BqX3+vrh/ZNOyuUef37/PppwDQxQO\nC/1QFBTmUUFKSjaRbFXXACC6kNiJHDMzMzMzs6LXhw4dKvpg+5l1XfLPI6ZjABA7acePXiqk\n9laW1RiHJSIlMzM9Os8vt2qCz+dXveji+ymoqUnTv6nlFiqkpKQQlfTgJd6/n5H/zLejqq9w\nlV2uKrtowF5B+GChwoLobaEvWO1XjW1XwYkE70/42Lhv+WS/5cJBL+Ny+aC8ujqHVPpv+ee3\nLl8cJN+4Zit5AZiGxA4AoKHhPd4xZubhLJX+c36t7tOjOw8YoBMQGHni8W8mRWtLBQnHTjwh\nxeFdWtUkEg6HQ5STk1OWtpHkL9Y92AfOnr7D72lenDQ+OnX6BZFBcYXmY3dfsBO6b13e6fn2\nK+/1XXNitoWG8Dw8ouzI4L3JbOvfRn09biFIPjbe2iM4w2HrxYNjy2d1RCRp2ddebt+VCy80\nRzuo1OT6AEQOEjsAAHFX+ObaiRMFJCjgfU55dS/mxJ4DFxPlui0+um1g2RzdD/HHLr/II3rw\nLI8o+cbRcHkukWYHlx4GbCIiiW7z1g3eP9DX3uW/BSM6qqRdD/191Q25nusX9BWe/lD4MiY8\nvPxDK1RNHWyM5egbtExNNShkT8AhExd9OSlZHVMTLU6jkX5T11mtH+HTeucSVyOJ58d/H73p\nmdDop7xhZytDoTZ4L9WIpBqbfzUI/Olg8JEMGSevoY2+PG32xZnWHlsfaTgvG6R0LyL8XnGx\ntGFPZ4tGRETKQ9esC+s23qNz2qSpQ7oZNeJkf0x8En/uaP6wS+udvjn/BUAMILEDABB3vLOL\nnc4SSUjLKipr6pu0c/xtn5eXezt14Qzl7uaRHtsyijfig0Z4BFH5Na2N3ENjjhjN/T107ohV\nWRxNE8vJO5f7jzAqNxLLi/rdI6r8uS3+eHJjXvNvRcayWrhj7vO5IWN6rfqczzf/48ntec1J\n9peV0ScVp82b20Pfk1Sb/+Ixd7fvdtu533vVSWHbTuWqDPPq//Vy2E83YhPyiN4eWzj0mFCx\n0thz6cF2REQk2eLXEzcN1y9dE7bSZ0NStpSypq5RBxvHX01xEzAQc6wGdvMzUSMlJXXmzBlb\nW9sfO9zb2zs9PX3v3r0V7h03blx2dnZYWJhw4cenP3aqOqGhllx1pXoUtb9688h/PkqidDP+\nDDwP+NtsJzAdAQCINvTYiY3Zs2c3a9ZMeCLzrVu35OS+OQICAAAAPxskduLh7du3a9as0dXV\nZbPLJgG/e/dOXf3Lnhbe5/qNrFIFuughEw/oJKsEv5DpCAAAqg2JnXiQkpIiojNnzrRqVbZC\nrWgolrmgAAAAQLRgmigAAABAA4HEDgBAjPHCXFmlpDhKjVv2HLI44lkVz1etTakxG2d6ulmZ\n6ymyWSyWY0hm1YcAQJ1BYgcAIO64vf2OHz9+/Nj+4KXDm7467O/WfVxkRtWH1Y6kqK0hF9+w\njRzszfEoLgDGYY4dAIC4k9Tt5OjYh4iIBgyzkjE3X7rn72NB/UYo1MfJTXxvpS6WIKKLkw6F\nx9fHGQHg29Bj94P4fL6BgYGlpWWvShUWFiYkJDAdLAD8PCTMunSUocL374sfxnpxkhZLfcJF\noRov13RhsfqUDpkmLGvLYrluv7dnuoNpY3mugpZRjzEb40sfUs2LX9SOK9l8QnRpF+CHI4O1\nWQo91j4qKDphrT9NFgB+HHrsflBeXt6rV6969uypra1dSbWoqKiv70gCAFB3Prx8mUPyRkaV\nfTR95fLsgRmTlu2I3dEk/+6OCUMnOxToPt/lIk9EXAu/A2v/sZg01LPnrUNDG/OfBw0bsz/f\nefe+mcb4AgEQPXhf1oiPj0+XLl0qqbBmzZq6S+xevHhx//79Xr16EZGkpKSvr+8vv/xSR+cC\nAFFWwMvMzCRBbtqLq2Gzl15Qs94wv5/09zTAt/M/7DdAhYhIa8E6711tV+w6vcPFXYqISLLF\nxD3Bl9oOGj9kQ5tVaZ4zo5THnQoZ2qQurgMAagqJnRhzc3PT0NDQ09Mr2lRTU6u8PgA0UFmh\nbgqhJRvcNjPPRkxp9X1Psm9nY6NSumFkZEQFr169JdIvLmk8MHj3RQv72Z0tCwtbLojZYK9S\ncTMAwDQkdmLMx8fHx8eH6SgAgHEyjmvOzu1M+Vnv7h5a/dvWtf2Hm92JGPk9Y7FKSkplG2w2\nmygnJ0e4gqKl54Bmm1c+kbabMrUTt5biBoBahzmvAADiTkKzdffu3btb2w+c+nf0fi/dlGMz\n5hwtXuzA5XKpoKBAqPZ///333WfI+mf2iLUvjDq1kzk/d2zo29oJGwBqHxI7AICGRKHPyjVu\nyql7fQMe8ImIDAwMKOPp04+lFd5EX3j6nW2mHp0weMNri+WHY05tGyJ13Gfw2n8Lqj4KABiA\nxA4AoGFR9fhjbgfW/fWLD3wiIq0BI+xkLq+asu1aYurHF9fCpnqsu/9dQ6mCl8EjxoRlOwbt\nn9WarTlgy+5JTWLnD/S9Wvqg6g/xx8LDw8PDLz3LI0q+cTQ8PDw8/MrL/Fq/MACoGhI7AIAG\nhmU8ddXYJv8d9ltzh0/UeMyuyGUWT353MGrSrMf4Q/LzQ+eYVL+t/HsrB005rTgqJHS0PouI\nSMFmzQFfs2crB0089amoyt3NIz08PDw8lpz+TBQfNMLDw8PDw+98Vl1cGgBUgSUQCJiOQSzx\neDwZGZm4uLjKb3ciJSV15swZW1vbHzuLt7d3enr63r17379/r6Wl9e+//7Zq1aryQ97c+rFT\n1YnG3/H1UR8u7WA6AhBD/EKmIxDSayLTEQCAaEOPHQAAAEADgcQOAAAAoIHAfewaGgGf6QiE\nfHzGdARQPeo6TEcgJCWR6QjKMzBlOgIAgGpDj51Ie/jw4YkTJ5o1a9apUyciSkysp2+862t1\nOq+NqZ9zAQAAQG1BYifS5s2bN2PGjLlz506ePJmINDU16/JsKW+TKljGlp306lNdnhUAaoIX\n5soqIyWnrteqx1D/Qw9rviY1YVlbFst1XyU3rEuN2TjT083KXE+RzWKxHEMya3xOAKgpJHYi\nrU+fPn5+fuPGjRsxYgQVP+enrgie/D12UKsRfx54Vnp3quyEE3/2thnktPsJlk4DiDJub7/j\nx48fP37s4LYV3r/wzix2/2Xk3g91ftqkqK0hF9+wjRzszWXr/GQAUC2YYwfFWC0WHDvQOfTv\nBYMHbm6jmpVNKwZ5xGd1mLFy3yRLbRbT0QFAJSR1Ozk69ineGOyu9Ubd8+je07whI+v2oa4m\nvrdSF0sQ0cVJh8Lj6/RUAFBN6LGDMtJatr/+Fhs+QfXBw/T/HsYrjb9y1G+2pbYM03EBwPdQ\nUFNjE4vNLv7h/ixigaeDRfPGyjLSXGUdMwef4PgM4eq5zyOXjrI20VbicmTVdFpbDV0dI7Sf\nnxS1bFBHXUUZBS2jHmM2xqcLHSkhga8QAFGDHjsok/Xq6NZNC3c+MuxsqvIPdc/f1s0+ZuKc\niTPt9eWZDg0AKlPAy8zMJKKCzPcJ51cvPpyrOWxkn+LP9zcJz5SsfZZP0FWXz095dGnbygnW\nCfx70eP0iYgKHm1y6DrxiozN5PmbrI3VCz48uhaZ8CKTuisVHXzHr+/45g7TV+/Uzru/x2/p\nZIcC3ee7XPCJACCykNiJn3Pnzr1+/VpRUVG4UEJCwsbGRkVF5YebFTzxc/EKazpi/bGl/ZL+\n1LlJU3dMXh29c7rfyC4JwfemtsBoLIDIygp1Uwgt3eI07R90ZotLyaeB1dz9VqX7bPsNMM3S\n7bl+291x/mZE6XvnzLmQZ7f17lkvnaL3uL3bcOGWk7XGPYic3JSIyNVJ//3/rP7adXqHizu+\nOgBEFd6d4ufXX399//69jEy5EVIWi/X3338PGDDgh5tltZi678g8dVUOESUVFUkb2Hgd6d7/\nPU8VWR2AKJNxXHN2bmci4vM+vbkdGfjHxN7O/KhTE9tIElFhUnSg/9o9524+fZ/By+cLBIV5\nxH/4UEBmLP7lU2ezuP19PHW+9R638PBoWvJaysLCjApevXpLpF8vlwUA3w+JnfgxNjYeNmzY\n77//XtsNK6urFr+SZMvJkmTRa2lVTenaPhMA1CoJzdbdu3cv3rBz7qfxTnv07Pn7hh0fppwb\nM8ey9/pcB1//bXZtdFXl2BKvN7vZB+bk5BJxP3/8yCNtHZ1vT5VTV1cv2+ByuUQ5OTl1ezEA\nUBNI7KAC7ac8usB0DADwo5RNTXXoxJ07j2lYp9hdIU/khh49vMSl5G5JybkfiZoREZGChgaX\nYhIT+dQRyyAAGga8lwEAGpgP16+/JmrUSIOIBAJB0TLZYryo/cdSSzYkejr0luNFbNouYo9x\nA4Afhh47AABxV/jm2okTBUTE56Ul3onctP58robb9OGGRNTB0VFz6+5lAYN3eLflvosNmeYV\nzlMoPVB5yKpVO7pO9O5s93Cep3VLDX7Kk2uRD1quDBrepDrn/RB/7PKLPKIHz/KIkm8cDZfn\nEml2cOlhUIc3UweAyiCxAwAQd7yzi53OEhGxpBW1dA3bDA1Yt8CnlxYRkaJzYGTQzOkBTs3n\nZ3G029iM3BjeebGVb8mRUsY+J6/prFi8es/ScX+mCxQ0DcwtPR0UvnWiL9zdPNJjW8lN7+KD\nRngEEZHt1rTzXsq1en0AUG1I7AAAxBh3+FHB8EprKFv4bLvsI1zST7BIuIXmzkt2Oy/56riW\ni26Xq0ckNThcMFi4wC44XRD8nQEDQJ3CHDsAAACABgKJHQAAAEADgaHYhuZzatV16g2bw3QE\nUD15onRnMv02TEdQ3qv7TEcgpEVPpiMAANGGHjsAAACABgKJHQAAAEADgcROnMTFxZ0/fz4p\nKSk9PZ3pWABAhGQ+PrHax6WrsbaKnLS0jFJjo86OY3/bceVtXvUOT1jWlsVy3VdQt0ECQD3A\nHDvxICkpKSEhMXbs2KJNgUDAbDwAIDL4L/aPsR+985VK14EjZ3ia6ilLZr9/Gh91aPOv27c/\niEtc04XpAAGgHiGxEw/q6uqFhYVFr+3t7Tt06MBsPAAgIvj3/nAbuTOp45J/Ti7uoFhaPHrS\nopUJ+wKuyTIYGgAwAEOxAADiK/fYytV38s0XbBfO6orIthy8aKRZydaziAWeDhbNGyvLSHOV\ndcwcfILjM744IO/54bmOZo3luTIqTbt7Bl5LK9tVNFb719XNXlZi85BxAAAgAElEQVTGGrIc\n7lcVqtM+ANQD9NgBAIiva+fOZVBrt/5GVVV8k/BMydpn+QRddfn8lEeXtq2cYJ3Avxc9Tr+0\nRryvwy3ToUv+nqqVdXvv0sVTbR7l3bg8q6VkaYWo2YNTpgceeWDdOOvmrukjZtg4ClWoun0A\nqA9I7MSVoaFhSkoKm138qG0Wi7V169b+/fszGxUA1Ku8168/EHUyMCgrEuTnZOUWT9wgCWlZ\nWWkJIiKrufutSuvY9htgmqXbc/22u+P8S/v03qqMunv8tzYsIurlYK2e2tTT3z/Ce09/udKT\ndZ6339+5CRGR5ZTdm28ZOApVqLp9AKgPSOzElYyMTP/+/R0dHYs2WSyWtbU1syEBQH2rYBnV\n+6Bejaf/U7yhPzPuZdHqicKk6ED/tXvO3Xz6PoOXzxcICvOI//ChgMxYxXXNhwxrU/KaNIcO\nt/M6GR19nfpblZSZ9+3bpPQ0cn36WUqGlFWoun0AqA9I7MSVjIyMubm5h4cH04EAAHM4enqN\niF6+fElkXFykNnDzlQ4ZRBkRkx3XlMyCy42ZY9l7fa6Dr/82uza6qnJsideb3ewDc3JyibjF\ndbS0tIRbbtxYhVJThR9lo6amJrQlqa6uXFqhOu0DQH1AYgcAIL469e6ttGn30SOPF88rnmbH\n1jbtrk1EKfeViEoSu9hdIU/khh49vMSlePYGJed+JGom3FRycrJQSW5SUtoXqVxiYmJZ/kg5\niYmfSitUp30AqA9YFQsAIL44TnNmm7NvL/f0v/FfJdUEAgEpqKmVZF3Ei9p/7MvnSt/Zu/tB\n6dDu+z1h5/nyNjYdhSrc37vrFr9k4+3O0POC0grVaR8A6gN67AAAxJiE6fwjoY/tRy/+peXp\ngaMGWJrqKUvy0pOfXTu5+wZx22gpERFRB0dHza27lwUM3uHdlvsuNmSaVzhP4YuWtNNC+znl\nL5nQUyvzzp6lv52kLisWucgJVdDJ3OvcT+DnY9U481aY3+LzkmUVqtM+ANQH9NgBAIg1CcPB\noTfvHlvqov7k0OqZY4cOGTVxYeDxV5oD1198fHlWKyIiUnQOjAxyzt7k1FxZtZndvH/abwyf\n8eUdUjr4n1xjfGONl5vL6GVXlAcGREXONZEUrmDhf3K9yc2AX91cxyyPVRskXKE67QNAfUCP\nHQCA2JM3cpqz2WlOJTWULXy2XfYRLuknWFTysuWi28Ubp9zXfrsN6WYD1p4aUHGFStsHgHqD\nHjvxk5ub++LFi7S0tOzsbKZjAQAAABGCHjvxk5iYeOnSJSI6f/78okVf/iQuyGMipm9Q0WY6\nAqgeaRmmIxDy6j7TEQAAiC0kduLn6dOnRGRhYeHs7Mx0LADwUygbqwUA0YahWAAAAIAGAokd\nAIAYuzrLgMXqvjH5i+KYSVosltXGlG8fmLCsLYvluq/g2zVSYzbO9HSzMtdTZLNYLMeQzFoJ\nGADqFBI7AACoSFLU1pCLb9hGDvbmskzHAgDVhMQOAODnkp+dk1+deia+t1Kf3zh3cMvELqK0\nugYAKoPEDgCggSsadd16M2Syvam2IofbbllCya6854fnOpo1lufKqDTt7hl4LU3oMAkJfEMA\niB2sigUA+BlcmuOe5Om36dzfhuz/8jSJkoiI4n0dbpkOXfL3VK2s23uXLp5q8yjvxuVZLSWr\nagwARBUSO3GVlpYWGRn54cOH0pLRo0e3bNmSwZAAQITldl0UsXaEVul2EhHRW5VRd4//1oZF\nRL0crNVTm3r6+0d47+kv961WAEDEoaNdXBkZGX3+/Dm+xK1bt1JTU5kOCgBElrm9vdbXhUOG\ntWGVbGgOHW4n8Tk6+nq9xgUAtQo9duLq9OnTTIcAAMyTkpIiKij48q4l+fn5RGw2u6xEU1Pz\n66O1tISTPU7jxiqEn4gAYg09dgAAYkxTU5PozZs35Usz37xJJxlNTcUqjk5OFr4BXm5SUhqp\nqanVdowAUH+Q2AEAiDFdOzsjenc47EJ2WZkgcc/ui3yOjV131rcPJCKiO3t3PxCUbLzfE3ae\nL29j07GOQgWAeoChWAAAcWY6dc2Yna6bHC2Sp0zoa67NzXget2/9XxdZHfyXDVWv6mDttNB+\nTvlLJvTUyryzZ+lvJ6nLikUupSsnPsQfu/wij+jBszyi5BtHw+W5RJodXHoYsCtrFAAYhMQO\nAECsqToFX73Q1m9lyF7/yWv/K+So6ptaztr126LhbaSrPLaD/8nhd6ct8Vr3JF1K22JgQFTA\ndJOye53c3TzSY1tG8UZ80AiPICKy3Zp23ku5bi4FAGqMJRAIqq4FX+HxeDIyMnFxcV26dKmk\nmpSU1JkzZ2xtbestsDsn6u1UVdMwYDqC8h7GMB2BqFLXYToCISmJTEcgwmwnMB0BAIg2zLED\nAAAAaCCQ2AEAAAA0EJhj19CwqloFV5/yspiOAKrH3EmE/m6iNmN+CADAD0KPHQAAAEADgcQO\nAECM8cJcWSx5r9p9Es2NeQasL6hPuli2P3mjFYtlF5xeqycFgNqAoVgAAPiaRI85+6eU3auY\n07w1g8EAQHUhsQMAgK+x9Lq6u7syHQUAfCcMxQIANFi5zyOXjrI20VbicmTVdFpbDV0dU3TD\n4WcRCzwdLJo3VpaR5irrmDn4BMdnfH14QU52bmE9hwwANYIeOwCAhqng0SaHrhOvyNhMnr/J\n2li94MOja5EJLzKpuxLRm4RnStY+yyfoqsvnpzy6tG3lBOsE/r3ocfqlRxceHa3MzcgolFTQ\n79jXy3fl3L76eJAYgOhDYicSHj9+LCVV0/8LPT29mjcCAA1F+t45cy7k2W29e9ZLp+h2NvZu\nw0t2Ws3db1Va07bfANMs3Z7rt90d529GRCTb1G7sYgtrcwM1yU/PYvetC/Ttd/H23vjwwU3q\n+RoA4HshDxAJrVq14vP5NWwkNDR05MiRtRIPAIg9/uVTZ7O4/X08dSq6SWFhUnSg/9o9524+\nfZ/By+cLBIV5xH/4UEBmLCIyGRccXFrVedjQniNN++2atSpu0IauInTHQwCoABI7kcBms3fv\n3m1jY1OTRpSV8VxuACjx+eNHHmnr6FQ0kzo3Zo5l7/W5Dr7+2+za6KrKsSVeb3azD8zJySXi\nfl1dpe9oZ41dm69eTaSuunUeOADUBBI7USEvL6+iosJ0FADQUChoaHApJjGRTx2/yu1id4U8\nkRt69PASl5Jpc8m5H4mafbOxgoJCIgkJLLcDEHl4mwIANEQSPR16y/EiNm1P/HqfQCAgBTW1\n0sUQvKj9x1LL9ubnl18Km7Rv89FPpN+tG6bYAYg89NgBAIi7wpcx4eGZwiVyLW0dhqxataPr\nRO/Odg/neVq31OCnPLkW+aDlyqDhTTo4Ompu3b0sYPAO77bcd7Eh07zCeQqlx2btHGi8TWaQ\ng0ULHTWp9OdxB7bsvJqqO/LvOR2/OjEAiBokdgAA4o4X9btHVLkS/bnXX67o4HPyms6Kxav3\nLB33Z7pAQdPA3NLTQYGIFJ0DI4NmTg9waj4/i6PdxmbkxvDOi618i4+VNrXrpRp2asvZrR8z\nctnKuiZdvTfN8x3frVG9XxcAfDeWQCBgOgaxxOPxZGRk4uLiunTpUkk1KSmpM2fO2NraVt4a\nl8uNiIiwt7eveWB3I2veRq1RVGc6gvKe3WI6AlFl6y1Cax2jNuND6ZtsJzAdAQCINsyxAwAA\nAGggkNgBAAAANBCYY9fQqGgzHYGQ1DdMR1CerdMTpkMok5rbgukQhBzeyHQEZVobMx1BeQ8u\nMx0BAEC1occOAAAAoIFAYgcVuL5Gp9OaGKajEEUxi3voLI5nOgoAAICKIbGDUilvk7K+Ls1O\nevWp/mMRLWmvEnO+Ls1KfJtS/7EAlMcLc2Wx5L1OCxV9vv6HtTqLY+QZ/qrwm8dVS/JGKxbL\nLjhduIz/8epfUxwt9FVlOTIqTVp2c/v9wueanQUAahESOygmePK358BWwwMPPMsuKcpOOBHY\n29rDKezJT337CcHD/c52feyXn0wozXuznh9YPqal7fi/Hv7U/zIgilIuzLaxXXBdd+aJmG3u\n+pI1a4ytZti6taGqUCuJh0Z16uG9M7H5oFmrN2/6Y+agtvykpNyanQUAahEWT0AxVosFxw92\nDv1rwSD3zW3UsrJpxaAB8ZkdZ6w6MMlSW4Ruclb/WK0mXIsyDwpYa2Ozt716ThZtsbZ+8Lnb\nmODzw+11f+p/GRA1/MSI8b0HBb/vtOz88YVdlGreoNqQHfeHCG1/3O3tGZbVN/jWwbGG0sVl\nM2p+GgCoPeixgzLSWra/Lok95K364N/0//6NV/S+EuE/21Jbhum4mMdp0nXG2v1XZinduvtf\n+t0HyjP3XF3vZa/LZTougDJ5T3YN6u6+PcNu8+UzX2R1uc8jl46yNtFW4nJk1XRaWw1dHZNB\nRJSwrC2L5br93p7pDqaN5bkKWkY9xmyMFxp4/WIo9kXon5H/tZ68YqyhNAn4/Hq7NACoPiR2\nUCbr5dF1c8xct+ZamKkomXXP39qt92y/My8zqz6yoct8dt5vvFO39XndLJRULCzyNwwyG/fn\n0bJBawCGZd0OdOo+KkJq4J6YoxNal/sxVvBok0MHR//zEn3mbzp4/EjwivFdBS9elL2tL88e\nuFXRa0fs0xfxO0ezj092mBzxjfd8zpXLNwRav+g/nNO3lTpHSkpatZnlmPWxKZiQACBCMBQr\nTu7du2djY6Ovr//1LklJyT/++MPGxuaHGxc88XP2DGs6cv3xZf2SAnVu0tSQKaujQ6cvGdHl\n4fZ701r8vGOOgod/du5/zGj8wv8FWiUu7xFHo04smBu5+fdpjh53D5/4rdXP+y8DIiNr3/yp\nxLXcdD1skN4Xf5Dpe+fMuZBnt/XuWS+dol32bsOFK/Dt/A/7DVAhItJasM57V9sVu07vcHGv\n4Mvh/bt3hfR53+RRjfstDIzooJJ2faef/3SbW5/irvu3Y9fRpQHA90FiJ07S0tJSUlKmTp3K\nZlfwIWpoaFiTxlktpu4/Ok9djUNESUVF0gY2vx7p3v89T+2nzl1YrUZFXx6vqSFNRIlFRZwm\n/aZtshuWkqPxU//LgMiQ6ebU/fHx80sn/m1zaLyxtNAe/uVTZ7O4/X08db71t9rOxkaldMPI\nyIgKXr16S1TB70c+n0+UlWO67tSeaYZERHYOnaRftZq1ZmXE/H3umLMBIBKQ2IkTDodDRDNn\nzpSRqYvPUGV1teJXEmw5WSpeCCetpin9zUN+EoqaGsWvJDkyciUTGDga6hzGQgIQJtHK59jm\nXq62U7yt+vOjD3m3Kv3T/PzxI4+0dXS+Pe1GSUloPh6bzSbKyang9j5EpKamRkRGffqU/YZs\n3tfBaFbczZsPyb19zS8DAGoOiR1UwGLqo4tMxyCaui44+4jpGAAqwjWbHHFBws12so+1Gz/6\nyESTotxOQUODSzGJiXzqWOMp1UpmZnp0nl9u1QSfzyeSkMB0bQBRgXcjAEDDwGkz8ciFTf3o\n9CRrl8AHPCIikujp0FuOF7Fpe2ItnKDzgAE69DjyxOOSAkHCsRNPSLFLl1a10DoA1Ab02AEA\nNBgckwmHL0h42EyYau3Mj4qYZiqjPGTVqh1dJ3p3tns4z9O6pQY/5cm1yActVwYNb/LdrUt0\nm7du8P6BvvYu/y0Y0VEl7Xro76tuyPVcv6AvZiUAiAr02AEANCTSrcaFX9zqKnV+uo1TwN0c\nkjL2OXktYqFV7vGl4/r3cx0zJyiWmhoqVL9BFqts3UUj99CYI/M6JoXNHeExbHZoovnknbEn\npxrhmwRAZKDHDgBAjHGHHxUM/6KMbTz2yLuxQnWaOy/Z7bzkq2NbLrotWFSuRGpwuGBw2WZG\nRgaxjdWEs0BpQxe/Ay5+NY4bAOoGEjvRwuPxsrKyvjUT+fNnPGsbAOpF2uNLsZd37L7H7jza\nAh1yAOIDiV3dEggEwcHB586dq7xafn5+UlISEZmbmz9+/LjyyoWFhbUWHwBAhf75o9/AE1oW\nY7ZtGa/LdCwAUH1I7OqWkZHR27dvU1JSKq8mEAgyMjKIqHnz5h06dJgxo+LHat+/f3/06NGS\nkpKVNJX56YeDrX0cWaYjKO8zuwXTIZR5/y/TEQhR+/SR6RDKvE1gOgIgIscdmXhmHoAYQmJX\ntx4+fFidalwut2XLlkTEZrM1NTUtLCwqrFZQUFCbwQHUqph9AYPJPXGwHtOBAAD8vDB1AgBq\nIvtVav7XpVmpGVV0U0PNZYb0YVVCa1oMJW+0YrHsgtPrJoDUmI0zPd2szPUU2SwWyzEks25O\nAwDfAT12APDjBInxzituaFn33uDYurgoN+XAiVMzozPHz/depMNocA2ejPWigwe9ijeyz/mP\n+vtlryXbx5X8T3BbtCL2G8PWraVUK5u+UQNJUVtDLrLbWzjYs8PC4+vmHADwfZDYAcCPY+n0\nuOavExQRZeN7o71ifhbFWPsmfW7ZNdivk70608E1eJL63d31SzbSU/4ietfU0t3dSrjOkB33\nh9RZACa+t1IXSxDRxUmHkNgBiAYMxQJAjXBUDWeMGXvFVebWK176qyRllzFXPbvZq+NHo0j4\ncij2WcQCTweL5o2VZaS5yjpmDj7B8RmllROWtWWxXMNeRC5ybaetICOn0arP3GOJfMr5N2xK\n79aa8nKqBh2GrIlLKz0Az4gFED348AWAGslMTlh7JHrTa+WeTblRpJd/YpvZ3U7L3bq6akkz\nHRp85U3CMyVrn+UTdNXl81MeXdq2coJ1Av9e9LjSjj+6s8RphpnbrA2jVT5eXL9o1QD3vIWN\nIg6r/Dp7k4/MyyPLfGf3k2z+MsxVkcGLAIBKILETJ0WrYrdv385ms7/YJSEh4eTkpKmpyURc\n8PMSJF7qvPKukX2f/3m1SDwUEEedTwzoFXnmzLTfg+/O9fkNc+xEjdXc/ValG7b9Bphm6fZc\nv+3uOH+zksJk/YmPDnvrERG5dsm+qjt7/cZhR56GuioTETnrvb7QLSjsZIjrYHx5AIgmvDfF\nibS0tIyMTEBAwNe7WCyWlpaWo6Nj/UcFPzOWTufo37trKkoSUWJREVu5n+Mgu55ZOejTEUGF\nSdGB/mv3nLv59H0GL58vEBTmEf/hQwGZlTwP1sLNrfSGNTqmpsoUb+3mqFxcIGFm1poKX716\nS6T/deMAIAKQ2ImTjh07ZmfjnqEgUriaJQmcpJS0XMm0XY6iHIexkOBbcmPmWPZen+vg67/N\nro2uqhxb4vVmN/vAnJxcIm5xHXV1oVUvHA6HlNTUpMoVUE5OTv3GDQDVh8QOAGpHV/dJj5iO\nASoVuyvkidzQo4eXuJRM5kjO/UjUjNGgAKBWYUkTAMBPQiAQkIKaWukUXV7U/mOpTAYEALUO\nPXYAAD+JDo6Omlt3LwsYvMO7LfddbMg0r3CeQk0a/BB/7PKLPKIHz/KIkm8cDZfnEml2cOlh\n8OX6LgCoJ0jsAAB+EorOgZFBM6cHODWfn8XRbmMzcmN458VWvj/e4N3NIz22ldwILz5ohEcQ\nEdluTTvvpVzZYQBQd1gCgYDpGMQSj8eTkZGJi4vr0qVLzVvjcrkRERH29vaurq5NmzatcN1r\nNT2Mqnk4tUfE/rh0zKquU2/e3GE6AiEmr5cwHUKZeJUlTIdQTvoHpiMQYjuB6QgAQLRhjh0A\nAABAA4HEDgAAAKCBwBy7hkZahukIhEiJ2ATqmyeYjkCIknrVdeqPXI2m0NcupUZMR1CeSA3F\nAgBUDj12AAAAAA0EEjsAAACABgKJHQCA2PucEPHHOMeOzTSVZKQ58hrNOvQdt2zfnTR+XZwr\neaMVi2UXnF4XbQNATWGOHQCAWOO/2De69+hdr1S7Dhkzb0KbJgqF6a/uXjoUNLJ9TGbaaS/F\nqlsAgIYDiR0AgBjj31/Rf9Sud20XXD7ze5ey2wKPm+23ZO+hd5L1Hk9+dg7JyojYuimAnwiG\nYgEAxFfu8ZWrb+e1nrdjWZcvHvYg02LIcEs5IuLFL2rHlWw+IbrkERH04chgbZZCj7WPCoiI\n6FnEAk8Hi+aNlWWkuco6Zg4+wfEZQg0JkqKWD+qgp8DlKulaDPQ/k1R+gDdhWVsWy3XrzZDJ\n9qbaihxuu2UJdXWxAFA19NgBAIiva2fPppPJFHcT1jercC38Dqz9x2LSUM+etw4Nbcx/HjRs\nzP585937ZhoXfQO8SXimZO2zfIKuunx+yqNL21ZOsE7g34sep09ElBM339Zh5bu24/8Ic2sh\n8fzE2tH937GITMqf49Ic9yRPv03n/jZk/5enWXeXCwBVQWInZho3bpycnPx1OYvF2r1795Ah\nQ+o/JABgTN7r1x+IOjVtWmktyRYT9wRfajto/JANbValec6MUh53KmRok5LdVnP3W5XWte03\nwDRLt+f6bXfH+ZsRfQz1DXioNOx49F+O8kRE9g5GvGZ2wV8mdrldF0WsHaFVi1cGAD8GiZ1I\nyM/Pd3d3Z7PZGRkZxsbGlTwrVl1d3cXFxd3d/YtyFotVK0+tBQBxUu3HMTceGLz7ooX97M6W\nhYUtF8RssFcp21eYFB3ov3bPuZtP32fw8vkCQWEe8R8+FJAZqzDmwpV8lZEjirI6IiIZ21ED\nmwRv+KJ5c3t7ZHUAIgGJnUj4888/VVRUpKSkli5dampqWklNDofTokULOzu7eosNAEQXR0+v\nEdHz58+JWlVRVdHSc0CzzSufSNtNmdqJW1aeGzPHsvf6XAdf/212bXRV5dgSrze72Qfm5OQS\ncT+npuZREx0d4YZ0ym8SEZGmJsZfAUQDFk+IBB8fnyFDhnh4eDRt2hQfkABQbZ3s7ZXp38Ph\n/1bVd5f1z+wRa18YdWonc37u2NC3ZTtid4U8kRsaeHjJqL7dLUxNWrZsKZ37sWSngpqaNKWm\npgq3lJKSUquXAAC1CYkdAID44jjOmd1W+v6KMYv+l1F+T86TvWGXsoo3Uo9OGLzhtcXywzGn\ntg2ROu4zeO2/BcW7BAIBKaipld6ghBe1/1hpIif5i3UPdtLZ03fKVsI+OnX6RZ1dDgDUFBI7\nAAAxJtFm3uHQEdp3lvdo9cvoRet37Dt4YPfW1XOGdWnWevjup4VERIKXwSPGhGU7Bu2f1Zqt\nOWDL7klNYucP9L2aTUREHRwdNd/uXhZwNSmHl/Ysep2HVzhPobT5RiP9pho9Wz/CZ/ft5Kzs\nD/f2Tx266ZksM5cKANWAxA4AQKxJGA7eGX/ryJJ+yvf3LJ8yeujwcfM3nU9t473z1l5PRaL8\neysHTTmtOCokdLQ+i4hIwWbNAV+zZysHTTz1iYgUnQMjg5yzNzk1V1ZtZjfvn/Ybw2cYlbUu\n+8vK6JPzja/P7aGvqmk+eIdg6m5fC4auFACqxhIIqr2qCoTweDwZGZm4uLjaXYvq6uratGnT\nSlbFdujQYciQITNnzvxWhWextRhOTUmJ2O3nX95jOgIhSupMRyCkbfZapkMo81Tnm3/ejHh1\nn+kIhNhOYDoCABBtWBUruhISEqKjozU0NIQLP378mJ6Oh28DAABABZDYia6pU6deuHBBXl5e\nuDA9PT02trJOuZzPdRzW92jdm+kIynsaz3QEQnKzmY5AWOvOTEdQJuMJ0xEAAIgtJHaiy8zM\nTFpa+vjx48KFHTp06Nu3L1MhAQAAgCjD4gkAAACABgKJHQCAGOOFubJY8l6n66JtwbvY7Uu9\nXbqZ6KvLySo3Me7kPH3H9RR+1QcCAGMwFAsAABXKPbt8XMAz2/5uk0cZqwuSb4YHbfLsFnHj\n5K2gXkpMxwYAFUNiBwAAFWLbrX2YaNxCrnhz9PghrWyMff5ascevl7co3a4HAMpgKBYAoAF5\nFrHA08GieWNlGWmuso6Zg09wfNmzxhKWtWWxXMNeRC5ybaetICOn0arP3GOJfMr5N2xK79aa\n8nKqBh2GrIlLK64uqVOW1RERsfRsrVsQ/+3b5Hq9JAD4DuixAwBoQN4kPFOy9lk+QVddPj/l\n0aVtKydYJ/DvRY/TL61xZ4nTDDO3WRtGq3y8uH7RqgHueQsbRRxW+XX2Jh+Zl0eW+c7uJ9n8\nZZirYgWNf4iJeUJyzubN6u96AOD7ILETMykpKeHh4Y8fP/56l4+Pj7m5ef2HBAAixGrufqvS\nDdt+A0yzdHuu33Z3nL9ZSWGy/sRHh731iIhcu2Rf1Z29fuOwI09DXZWJiJz1Xl/oFhR2MsR1\n8JdfD4I3ob/OPydot3xRf5l6uBAA+CFI7MRMly5dUlNT09LSviiXkJDIz89nJCQAECGFSdGB\n/mv3nLv59H0GL58vEBTmEf/hQwGZsYprWLi56ZXU1jE1VaZ4azdH5eICCTOz1lT46tVbIv1y\n7aacmeIw7rikW0j4XFPJeroWAPh+SOzEzL59+5gOAQBEVm7MHMve63MdfP232bXRVZVjS7ze\n7GYfmJOTS8QtrqOuLrTwgcPhkJKamlS5AsrJyRFuVfDx1BTb/kGpff6+uH9kU0zNBhBlSOwA\nABqM2F0hT+SGHj28xIVdXJKc+5GoJnPiBO9P+Ni4b/lkv+XCQS9jdtUHAACTkNgBADQYAoGA\nFNTUStMvXtT+Y6k1aS/52Hhrj+AMh60XD45FVgcgBpDYAQCIOxareAJdB0dHza27lwUM3uHd\nlvsuNmSaVzhP4Yebzb4409pj6yMN52WDlO5FhN8rLpY27Ols0ajmUQNAHUBiBwAgxj5//lw8\nMY6ISNE5MDJo5vQAp+bzszjabWxGbgzvvNjK9wfb/nQjNiGP6O2xhUOPCRUrjT2XHmxX08AB\noE4gsQMAEF+F9+49JGrWrGlJgbKFz7bLPsJV+gkWlbxsueh22QYREVltTBZsFC6QGn5UMLz4\ntc6sq4JZtR8zANQhJHYAAOIo/e7xo5fiItZvT+L2nD9Ar+oDAOBngMQOAEAcvdwzY+z6FB0z\nJ78tgROR1wFAESR2DU1aEtMRCLm6l+kIylPVYjoCIVkZVX7I88oAACAASURBVNepP2+fMR2B\nsO5MB1COgVnVdZjQdsWTwhVMBwEAogaJnWh58eLFrVu37t27R0R37tyRksJ/EIiNmC3TB5N3\n4ngjpgMBAPh54RbiomXUqFG2trYWFhYWFhaamprKyspVHwPApM+vPuR+XZr1ITWl/mP52WSG\n9GFVQmtaDKXHBi9ZEnY7r7pNFtwK9upvZWaopSLLkVXVNe4yYP7Om5/q8iIAoHahQ0i0zJgx\no/R1YWFhQkICg8EAVEnw4qLzzAtajoM3DOlUXJSTdGBv2MwTGePXLl1kyKr0aKgZGetFBw96\nFW9kn/Mf9ffLXku2j2tdXMJt0YrSdwT7+SkbzBreVrpaTRa+vv+goFnfX10NtVWlMl9fP7hl\nzaiuJ5/GxPt3xLcFgFjAWxUAfhzL0OnaX82CdofbTIhur5ybRZHW419+NusTvNnWXhNZXR2T\n1O/url+ykZ7yF9G7ppbu7lZCVV5+Z5Mcl/VxLmWbY71d1c1Mf/9rR6x/x541CRUA6guGYgGg\nRjiNTGZMX3RlhNytJ9npT14qD19wdZaDvWb1OoigLl2dZWA4+39EZ8YoFA3Otl3xtHhX7vPI\npaOsTbSVuBxZNZ3WVkNXx1S4mkdSV1ebCLN9AcQH3q0AUCOZiTfXhoZveqbRs5VcFBnl711m\ndt12+ag+rjpcpkP72bVbGHOF49RjueLqB6HuskQkraJDRFTwaJND14lXZGwmz99kbaxe8OHR\ntciEF5nUXan4wMLcrJz8Ql7aq/jwJX9EK1kGTOjC3FUAwHdBYid+Tp8+raGh8XV569atuVx8\nlUK9Erw42nlWnNGAof+bbZ64Y3oc9ToxZlBk+J5pU5feXbPsN8yxYxRHRUdHhUMko65nYCBf\nWpy+d86cC3l2W++e9dIp+g+ydxte7sBT4zWdQrOIiNi6TgHn90w1weAOgLhAYidmLl686ODg\nUOGusLCwYcOG1XM88JNjGfaODnbUVJEiosSiImn1fkOn2Dn8l6OCrE4k8S+fOpvF7e/jqfPN\n/6BfFp674pWb+eH59SN/Bkzr3Sf7TNT8jpz6DBIAfhQSOzFTdAOUtLQ03AkFRIOspkrxK0k2\nR65k2i5HRRF5gIj6/PEjj7R1dCrphFNp0bV7CyKy6tPfo62EkbPvrO2jL3k3rrcQAeDHoX8d\nAGpHV88VjzybMx0FVEVBQ4NL7xIT+dWr3blzKyp8/Ph5HUcFALUEiR0AQIPF4XCIcnJyhIok\nejr0luNFbNqe+HV1QWFh+XxP8PbYiZvEat68ad3GCQC1BUOxAAANlpapqQaF7Ak4ZOKiLycl\nq2NqosVRHrJq1Y6uE7072z2c52ndUoOf8uRa5IOWK4OGN8kI7m++W9Gjd9tmTTQ4OR+exIWH\n7P9fTqvpS0djHBZATCCxAwBosFhWC3fMfT43ZEyvVZ/z+eZ/PLk9rzlJGfucvKazYvHqPUvH\n/ZkuUNA0MLf0dFAgItlOri7RO89tOxuc/CmLJa9paGY5K3TunBHt5Ji+EACoJiR2AAANgPKE\n84IJFZQ37rfiZL8VX5Zymzsv2e285Mti6XZjAvePqYvwAKCeYI4dAAAAQAOBxA4AAACggcBQ\nbEMjIcl0BEKk2ExHUN6nZKYjEFnK6kxHUObNLaYjKC/9A9MRCGnWjekIAEC0occOAAAAoIFA\nYgcAAADQQGAoVnQVFBRkZGTEx8cLFz5+/JipeABABPHCXGVGRBS9luTIKyo3MjBp27W3x9ix\nHu01RGlmBgDUCyR2oishIeHKlSsdOnT4eldubm79xwMAoorb2+/g5PYkKMj+78Pr+/9E7vEf\nsnnNhoUHI5daqzIdGwDUKyR2oisyMvLTp0+SkuV+c9+7d8/S0pLDwQPWAaCUpG4nR8c+JVvj\nZv22cMdQK89lbmNMnkYMEaGFMQBQ5zDHTnRJSEioq6urlKeoqMh0XAAg6mSMxmwPGCCfcWz1\n32WTNz5d3+LTx7SJEldaVrVpJ/eFhx+X9vwnLGvLYrluv7dnuoNpY3mugpZRjzEb49PLGhQk\nX1ztaWOioybLkVFqpG9q6R4Qy6uVlgGgdiGxAwBogFScXC0l6fbly/8RERHv+mLrHhN2Jrad\nuulgxO5Vg1SvrhzQdcCOV0JHXJ49cKui147Ypy/id45mH5/sMDkis3jXm6DBfedHyQxcFnLi\n3OkDW5b/+otM+qd8qoWWAaCWYShWLBkYGCgpKUlJlf33SUpKbtiwwcHBgcGoAECEyBkYqJPg\n3btkIkX6GLpgxV1u/wOXd3moEhE5uHSX69DGd97v0SP+tin+IOHb+R/2G6BCRKS1YJ33rrYr\ndp3e4eIuRSS4+U9sjunigCWjjYuq2rsNKzlNzVoGgNqGN5ZYysjI8Pb2NjQ0FC40NzdnKh4A\nED0CgaDkZWFM9OU8ucGj3UuXUki09BzdzXdqdPR9smlbVNTOxkal9GAjIyMqePXqLZE+Ecu8\nU0fO/kBPH/YEF5seXdsZKErWUssAUNuQ2IkrV1fXzp07Mx0FAIiqzJcvU4nVTluLiD6npuaR\nVuPGLKH9WtraLLqXmlpaoKSkVLaXzWYT5eTkFG0ZTDkSxfZfGfKn95a5WRLKzXsOmrHyD+8O\nKjVvGQBqGebYAQA0QGnHj14qpPZWlopEpKCmJk3vk5IEQhWS370TkJqaWrVak2z0y6SNx268\nyUh7ce3g4i7JoT72k49m10bLAFC7kNgBADQ0vMc7xsw8nKXSf86vLYiIJLvbWkpnHt95uHQ5\nquBxyM5YamRj0+a7GpZUNOjoOm3jlO706ebNl7XZMgDUDgzFAgCIu8I3106cKCBBAe9zyqt7\nMSf2HLiYKNdt8dFtA4u7zTRG/j4vqIf/aMtRz+d4mMq9v/z3klXxSv22L7SpzpfA++CBTmcM\nBvfrZKzXSC73Tdz2NZdZ+hNsW9S8ZQCobXjnAQCIO97ZxU5niSSkZRWVNfVN2jn+ts/Ly72d\netntzbkd/S5cbrzQN2id976P+bJN2tjMCf9j8YDqrV+QN7Nsd3L/jiUhr5Iz+PKNDMzs/U/6\nzrBk17xlAKhtLKF1U/AdeDyejIxMXFxcly5d6vO8t2/fbteuHRFdvXq1wsUT/+yqz3CqIM1l\nOoLy/kutus7PybZtJNMhlDl6oR/TIZSjoFJ1nXpjO4HpCABAtGGOHQAAAEADgaFYMZOdnV30\n4s6dOxX22IlUp1RmBtMRlKeqyXQEIuvNE6YjKCNSPWQAAOIFPXZiplu3bvfv3yfcjhgAAAC+\ngsRO/DRt2pTpEAAAAEAUIbEDABBjvDBXVhkpOXW9Vj2G+h96mFVSIT02eMmSsNt539dswa1g\nr/5WZoZaKrIcWVVd4y4D5u+8+am2gweAWoc5dgAA4o7b2+/g5PZEgvzM9wnnt6xZ7H76zp6E\nQ0MaEVF6bLCfn7LBrOFtpb+jxcLX9x8UNOv7q6uhtqpU5uvrB7esGdX15NOYeP+O+NoAEGV4\nhwIAiDtJ3U6Ojn2KNwa7a71R9zy69zRvyMgfvuMQx2V9nEvZ5lhvV3Uz09//2hHr37FnDYMF\ngLqEoVgAgIZFQU2NTSw2W4ro6iwDw9n/IzozRqForLbtiqdFlfiJZ/zc2+sqcLnK+h2HLD9/\nO9CKxbILTv9Gm5K6utpEUlLoDAAQcXiTAgCIvQJeZmYmERVkvk84v3rx4VzNYSP7SBG1Wxhz\nhePUY7ni6geh7rJEJK2iQ0SUdXmWdb91aV0mr9rt2Ezi1dk/PQe8KCAy+aLZwtysnPxCXtqr\n+PAlf0QrWQZMqNcbsgPA90NiJ6527dp18eLF0k0JCYlBgwbp6ekxFxEAMCUr1E0htHSL07R/\n0JktLipExFHR0VHhEMmo6xkYyJfWeB+65M+nGl7nzwfacomIejuaFhh13fBVYndqvKZTaBYR\nEVvXKeD8nqkmGOUBEHFI7MSPtLS0hobGlStX2Gx2aSGLxWrbti0SO4CfkozjmrNzOxMRn/fp\nze3IwD8m9nbmR52a2EaywuqFsZf+KVD3HGxbOgWP3WWIu8GGNV9W/GXhuSteuZkfnl8/8mfA\ntN59ss9Eze/IqbvrAIAaQ2InfiQlJT98+MB0FAAgOiQ0W3fv3r14w865n8Y77dGz5+8bdnyY\nckXVP6em5pGWlpZwmaZmBQ9mUWnRtXsLIrLq09+jrYSRs++s7aMveTeu7fABoPagWx0AoIFR\nNjXVoZw7dx5/Y7+CmhqbkpOThcvev39faZsKnTu3osLHj5/XVpAAUCeQ2AEANDAfrl9/TdSo\nkQYREYfDIcrJyRHaL9nNsrtUSsT+aF5JScG1/YdeCtUQFBbyyzUpeHvsxE1iNW+OB98AiDYM\nxQIAiLvCN9dOnCggIj4vLfFO5Kb153M13KYPNyQi0jI11aCQPQGHTFz05aRkdUxNtDiao5ZM\nXmezfrC9/PKZjs0kXp3dsORIoRaRhETxj/2M4P7muxU9erdt1kSDk/PhSVx4yP7/5bSavnQ0\nxmEBRBsSOwAAccc7u9jpLBERS1pRS9ewzdCAdQt8ehXNoWNZLdwx9/nckDG9Vn3O55v/8eT2\nvOYk13NN9AnFaQuCp3sEsTRM7Dw3B3dfYLdUWbl45axsJ1eX6J3ntp0NTv6UxZLXNDSznBU6\nd86IdnKMXSMAVAtLIBAwHYNY4vF4MjIycXFxXbqI1n2dTq1nOgIhmRlMR1CeagWzw4GIyFZN\nhP5uolKnMR2C6LKdUEcNvw60NJqW4//i2hz9OjoDANQL9NgBAPyE/hc06TzXtpOxtnz+h0eX\nQv5YdVlpcPgYZHUA4g6JHQDAT0hW8tP5dVPWvfqYkSulrGdmPfPw74vcNJiOCgBqCkOxP0hk\nh2ITopiOQEj2Z6YjKK8gl+kIhKiL0s2kn91iOgIhrUXsIfMCftV16k0TM6YjAADRhtudAAAA\nADQQSOwAAAAAGggkdgAAYuzqLAMWq/vG5C+KYyZpsVhWG1Nq2rzgXez2pd4u3Uz01eVklZsY\nd3KevuN6SrnR6RvzDFhfUJ90saYnBoAfg8UTAADwLblnl48LeGbb323yKGN1QfLN8KBNnt0i\nbpy8FdRLSaiaRI85+6d0LN3kNG9d/6ECABESOwAA+Da23dqHicYtSu5LPHr8kFY2xj5/rdjj\n18tbvawaS6+ru7srIxECQDkYigUAaOAEyRdXe9qY6KjJcmSUGumbWroHxBY/JjZhWVsWy/Wv\nq5u9rIw1ZDlclabdPQOvpZUeKqlTltUREbH0bK1bEP/t2y/HfokKcrJzC+v4SgCgKkjsxNLn\nz5/TyktPT2c6KAAQTW+CBvedHyUzcFnIiXOnD2xZ/usvMumf8oUqRM0evFt7xpEH75MfHp2m\nfn6GjeOahG+laB9iYp6QnLl5s3KlhUdHK3Nl5bgcRYOug5edfJX/jaMBoK5hKFb88Hg8JSWl\nr29AuHPnzhEjRjASEgCILsHNf2JzTBcHLBltXFRg7zasfI28zvP2+zs3ISKynLJ78y0DR3//\nCO89/b96MKzgTeiv888J2i1f1F+mtFC2qd3YxRbW5gZqkp+exe5bF+jb7+LtvfHhg5vU4UUB\nwDcgsRM/BQUFAoFg586dJiYmpYUsFqtNmzYMRgUAIopl3qkjZ3+gpw97gotNj67tDBQlv6hh\n3rdvWRIm16efpWRIdPR16m9VvlrKmSkO445LuoWEzzUVasJkXHBw6YbzsKE9R5r22zVrVdyg\nDV1ZtX81AFA5DMWKq1atWlkIad++vbS0NNNBAUB9k5KSIiooKPiiOD8/n4jNZhMRGUw5EhXo\noXbtT+++HQ3V1FvYTth8I024spqamtCWpPr/2bvzuJrSPw7g31PdFu1KpU2yZCtS1pFWElEh\nshNjlGUsg5hMSfb1Z8pWqYimEdLYhSyDQdnJkiwh0Ub7cu/vj7bbonJb7r35vF/3j3ue85xz\nvudS99vzPOd5lBUoJSWlwvk4n07NtbD3TRmy52LYZN2avjkUh04d0Yre3biRWJ/bAgAeIbED\nABBiqqqqRG/fvq1Ymvn2bTpJqarKERGRqMpPc3wib7/NSEu4ecijb1Kwq/XciOzy2omJ3ElY\nTmJiasVcj/PxuKuZg++nwbsvHpqhx6otpMLCIiIREXy9APADfvIAAISYlpVVR3p/JOQiV6LG\nSTx4IJotYWE1oGJfqKicTi/7+T7zBlBqbOyr8vKHofvvlM05/G5fcBRHxsKidFY6TlLkL2aj\ndqcN8YsO/7lTlX4BTkFBxecsPvy1MyKV2vTvjyF2APyAMXYAAMJM/9dN0/bZ77A1Spo3a2h3\ndcmMl9f/2rYrmjH28h6vTET00X/M8DM6TsN662mrSOe9vb5302WmzSzLDuWn0MwMHTGMs9LV\nrHXmnZCVHlGifde52xU/OZEdvcjc0e9pqxHeY+UfHAt/UHKEeNuBI4xUiIiy9o3RC5Aaa2PU\nQVNJLP3l9b9377uRojV5z5JeBAB8gMQOAECotRzuf+Nij5Xrg0K95m7+UiTRso2+6W/7/3Cf\n2K24eU3GwNTwZFigZ9DrpAy2jIqOgbXXyRULTbl6VI28Tk66N9/j5/89TxdTNxq7JWjLgi4l\nT0ek3r4Wl0/0LvL38ZFc15Sffi7d34qISFzfalDLkFO7z/p9yshjKWh16eeyw23FL/1Vmur2\nAaACpuqsGVAXubm5UlJS169f79u3bxNfOjMzU1ZW9tatW8bGxlX3xp1v4nBqkv2V3xFUVJjH\n7wi4KGvzOwIu8Xf4HQGXrgP5HUFFHHbtdZqMhkEDnzDOu0fnFTqhBRFO+DMfoFnAGDshU1hY\n6OnpSUT5+fn8jgUAAAAEC/5GEzI3btzYvHkzESUkJPTv379qhUxBWoFCSobfEVQkrcDvCLhk\nJPM7Ai6MIM039v4pvyOoqKsFvyMAAKgzJHZCRl5evviNnp4efyMBgGagk/tdjju/gwCAhoOu\nWAAAAIBmAokdAEBzkLh9oCjDMN08n/A7EgDgIyR2AADNwPPAvVfYRPQocO9/gvQcLwA0LSR2\nAABCj3M7IPAetRk2rBu92RcQVcDveACAX5DYAQAIu8ILAfsSSG/qul3O/UWS/9p7gmt9sTjv\nHgxjv+vGzhlmeq1aSEgq6g5w3n4z7TsqAIAQQWIHACDkck4GhH5gejlP66Y5yXkw62tEwKHU\nijXOL3Y6oL7w6KOPSU8i5itHLbSw3RRX9F0VAEA4YLoTYbVs2TJFRUXukkWLFvXp04df8QAA\nv6SFBxzNELOcPrkNEY2dPmL+6YiAkA9T5rUur5Lfxy3Ma4QGEZHpvAM77+jYenkdczk4UrrO\nFQBAOKDFTigNGDBAS0tLkYuSkpK0NH4FA/yAkg4EnMyVGurspEZEJDPC2VG56Mre4OfcdboP\nHapRtiE9ZJip6NcLF259TwUAEA5osRNKERERSkpK/I4CAATAi+CAy4WyoxzNOenp6UREfUaP\nVA3cs3dvjNtao9JKFX9hiCorK1BKSgpXUa0VAEA4oMUOAECI3dm79y6HvoZPal3afq88bM9H\noufBAZfLB8klJiZyHZOTmJhaKZWrtQIACAckdsLk7t27Bw8e5HcUACAwiq74Bz+jds77L1YQ\nschY5EPo3lM5pfUehu6/Uza73bt9wVEcGQuLXlwnqrUCAAgHdMUKk8WLF0dHRxNRTk5ObXUB\noPnLPRVw8D3Ta/2yiWbtK+zQnzPYZ+qhgCPbbScQEZFmZuiIYZyVrmatM++ErPSIEu27zt2O\ne1RurRUAQDigxU6Y6Ovrm5iYEJGUlBS/YwEAvvt6OOBQurjlL9PaV96jNOaX0YrZxwP++li8\nbeR1cluX2C0/O9hPW3NNaeyW8yeWdhHlPqDWCgAgHNBiBwAgpGQnHM2aUP0uKfuQVE4IEVEc\nERGJtxu1+dSozd8+V60VAEAooMUOAAAAoJlAYgcAAADQTKArtrlRVON3BFw+veF3BBW1VOd3\nBFzEWPyOgItaW35HwIUtYCtZxf/H7wi4dBvy3Yd0cr/Lca9XBQAQImixAwAAAGgmkNgBAAix\n3BB7hmEYiX7bXnIXJ20bwDDdPOOaNBbO+2t7V7nY9e/SRlm6hYKGXu8RCwJvfWbXfiAANBgk\ndgAAwi//xmr3I1/4HETe2TUzt0Tndrafu3rHjnXzrOXu7nDu33vuuQw+xwXwI8EYOwAAYacy\naIjmhb9+37jYbpUhH2efY1ltfpKo16F0XuOpv4zrbKHnumvdwZWDXJT5FxbADwUtdgAAwo7p\nsmDtZLW4rW57k75RI+/liVVTzLuoy0tKtFDS7Go2fuPV4na0+GPLnW2M2rdWkBKXVNA0sHH1\njylvYIvz7sEw9iEJJ9ztDdVlpaRbdR6yNDKRTTmPQ+YN7qoqI91Sx3jcputpJdVFNcuzOiIi\nRtvSvAOx3737VlQA0ODQYgcAIPxaDPb6wzLUxdPrwsQdFpVXpil8usOm3+wrUhZzl+0w11Mu\nTH5680RcQiYNkCd6Gxcvb+66ZpaWskzB56eXAtbPMo9jP7gws03Z0fc8hy80cPjtf1MVP0Vv\nc98wanT+7yrHjij+vHiHq9Sro94rFg8Tbf8qxF6umqiSr159TtIjurdr1HsHAC5I7ITSpUuX\n5OQq/xrt3bt31UIA+EFozlg/d0uvrUv/t+CmWweGe0966JIlF/Ot/O6fnaFZvMPaYWLpTrOl\nYWZlNS2HjdLP0hq4LeD+TC+D0sKkNrOfHnHRJiKy75t9Q2vxNp8JR18E2ysQEY3QfnOxv2/I\nySB7p8pfJ5y3wT8vO8cxXOM+EmsgAjQZJHZChsPhiIqKTp8+nWGYSrt2797t6OjIl6gAgP/E\njJatdvQbs949fGYY928C9uVTZ7MkR7o6a1b+pUFEVPThwnavzQfPxb74mJFbwOZwivKJ/eQJ\nhwxKaxs5OGiX1tbU11egGHMHW4WSAhEDg65U9Pr1O6I2Fc77+cw8m5n/iDoEhS/Vx6KzAE0H\niZ2ge/XqFZtdMl1AWlqatLR0YWEhf0MCAMGk6LjardfRZb+vXeywqLz066dPuaSuqVndkOq8\nq0tMB2/Ls1nhFWDVTaulNEvkzU4H6+05OXlEkiV1lJW5HnyQkJAgeSUlsQoFlJOTw31WzqdT\n8yxH+qYM2RMdNlkXQ7kBmhISO4GWmZnZtm2FNQFkZWX5FQwACLz289bP+NPCx81vjG1ZmWyr\nVpJ0NTGRTb2q5FjX9gc9lx4fccTTrnQllKS8T0T1GRPH+Xjc1WL07lTr3RcPzdATpAVWAH4I\n+FNKoBUVFRHRP//8Ex8fHx8fP3Xq1AEDBvA7KAAQXFLmHp7Woue9PM5mlRaJDLQZLJ17bMfe\nxKrVORwOySoplaVfuefDIlPqcXlOUuQvZqN2pw3xiw7/uZN4Pc4EALxBi50Q0NDQ0NXVJSJF\nRcW0tLRa6wPAD0x12roFm3t6n0oi6lpcojBuw4bAfrNd+lg9cXM279SK/fn5zROPOq33nahh\nbGur6nfAe4tToEsPyffXgubPCM/lvVcgO3qRuaPf01YjvMfKPzgW/qCkWLztwBFGKvW/MwCo\nAyR2AADNimiPJWvG7Rp58HNZiZie68mbmus8Nh5cNfPPdI6sqk53U2cbWSKSG7H9hO+iBVuG\nt1+WJaHezWKyT3gfD7MVPF459fa1uHyid5G/j4/kKpaffi7d36o+twQAdcZwOBx+xyCUcnNz\npaSkrl+/3rdv38a7SkZGhoKCQmxsrKGhIREtXLjw5cuXERERNRwS/2/jhfPdPr3hdwQVtVTn\ndwRc8rJqr9NkGEEalMEu4ncEFYkI0jOd3YbwOwIAEGyC9OscAAAAAOoBiR0AAABAM4Exds2N\ndEt+R8Dl1YPa6zSlrIza6wBU0qE3vyMAAKgztNgBAAAANBNI7AAAAACaCSR2AABCrfDDv3vm\nDe+lp9myhYSMska7HuaOrmtPv+N3WNVIueqzyNnBrLu2HIthGNugTH4HBNAMIbEDABBiyYen\n9DT5JeRtB8elW4MOBmxwm2GlkXxqT+RzfgdWjQ/n/YKi37I62lh3b8HvWACaKzw8AQAgvN4E\nrT+Y1GrKqX+DhkiXls1dtjEvr4CfUX1DlxV3UjxEiCh6zuHwGH5HA9A8ocUOAEB4paamEqm1\nayddoZSRkChfpzX+2HJnG6P2rRWkxCUVNA1sXP1jyp8Pj/PuwTD2IQkn3O0N1WWlpFt1HrI0\nMpFNOY9D5g3uqioj3VLHeNym62VLGXKSojc6W3TRVGohISWv0kbfdPSWa7ncp9r74OACG/3W\nMpKyah1NpvnEpHOFJSKCrxyAxoYWOwAA4dXJxKTV+qA/Z7q18Zw6tF8nZfGqVd7Gxcubu66Z\npaUsU/D56aWA9bPM49gPLsxsU1bjnufwhQYOv/1vquKn6G3uG0aNzv9d5dgRxZ8X73CVenXU\ne8XiYaLtX4XYyxG99XUauizB3N07aKCuXEFK4tNbpz+nFhBJlp7q8uIxGXO8A68FahTcD5w1\nfq5NodbL/XYyTfJZAAAhsRMuDx8+vHTpUsuW1UxVJyoq6ufnZ29v3/RRAQD/SA7bdNj701Tv\n9VPM1hNLXlu/v6WN/WRXZzP1st/uZkvDzMrqWw4bpZ+lNXBbwP2ZXgalhUltZj894qJNRGTf\nN/uG1uJtPhOOvgi2VyAiGqH95mJ/35CTQfZOYpzYf6/l6Hts8ZyqV3yktcOEivGwrbyOrByl\nSESktnyry/4e6/afDrQbja8agKaCnzZhsnr16mvXrqmrV7/iqYmJSRPHAwD8p2Ty+/Gns59f\nP3vmwrWb/105H7b6VOCfe/44c2VlXykiIir6cGG71+aD52JffMzILWBzOEX5xH7yhEMGTMkp\njBwctEtPp6mvr0Ax5g62CiUFIgYGXano9et3RG2Y7r17SYRtd3ZlzbKzMOlnqCNXeSFdQwsL\nxbKNjh07UmHxkY34AQAANyR2wqRXr169evXidxQAHnMHDgAAIABJREFUIGjEFDqYjOlgMoaI\nij5G/WY9dJv3ol3O/y5oQ5R3dYnp4G15Niu8Aqy6abWUZom82elgvT0nJ6+8A1VZWbn8XBIS\nEiSvpCRWoYBycnKIiHTmHT3P8lof9KfL7qVZIgrtB45duH6ti3F5LicvL19+KhaLVXYkADQN\njGQFAGhGRFWtFk4xJPaDB4+IiOja/qDn0uO3H/GcMnSAkX6XTp06ied9qsfpVX6a4xN5+21G\nWsLNQx59k4JdredGZDdQ7ABQf0jsAACEV3r8o3d5FYsyYmLiidTU1IiIiMPhkKySEqt0b+75\nsMiU+l9XVE6nl/18n3kDKDU29lX9zwcADQRdsQAAwuuVn12vANnh40dbGeu1li5If33nuN+u\nIymKg9fP7ElERMa2tqp+B7y3OAW69JB8fy1o/ozwXFler/bRf8zwMzpOw3rraatI5729vnfT\nZabNLMsOdT0+OSbyckI+0aP4fKKk2xHhMpJEqsZ2Jjqs2g8GgLpAYgcAILzaTdy4gR1x5uL+\ndQfffUzLE1PQ6GjkuHr98gXDdYoryI3YfsJ30YItw9svy5JQ72Yx2Se8j4fZCt6uJmNgangy\nLNAz6HVSBltGRcfA2uvkioWmdc7K7u+c7BhQOolejO8kR18isvRLi5qhUNNhAFB3DIfD4XcM\nQik3N1dKSur69et9+/ZtvKtkZGQoKCjExsYaGhrW8ZCkJ40Xznd7dInfEQDUW4fe/I6Ai3ZP\nfkcAAIINY+wAAAAAmgl0xTY3Dy7yOwIuHDa/I6hIXrn2Ok2mIK/2Ok2mhRy/I+CSm8XvCCpK\nfsnvCLigxQ4AaoYWOwAAAIBmAokdAAAAQDOBxK5eCgoK+B0CAPzgCj/8u2fe8F56mi1bSMgo\na7TrYe7ouvb0uwY6e5KPGcNY+aeXbqdc9Vnk7GDWXVuOxTCMbVBmA10HABoGEjseFT9NnJGR\nUWtNAIDGk3x4Sk+TX0LednBcujXoYMAGtxlWGsmn9kQ+b6Dzs5Tadu3atmXZmrAfzvsFRb9l\ndbSx7t6igS4BAA0ID0/wiGEYqrTCIgBAU3sTtP5gUqspp/4NGiJdWjZ32ca8vIbqTVAaF/hw\nHNd2lxV3UjxEiCh6zuHwmAa6CAA0GLTYAQAIr9TUVCK1du2kK5QyEhLiRESUe2q6MqM8/VQu\n99632weKMd1WPSYiivPuwTD2ex8cXGCj31pGUlato8k0n5j08sqVu2JFRPC1ASDI8BMKACC8\nOpmYtKL7f85023cp7nN+ld2SQ36dqZcS6hOaWlbEebBrxxVRi9kzu5QVXV48xk9uRuC1Fwkx\n+6ay/plrM/cYhs4BCCkkdsJtw4YNzs7Obm5uy5cvf/bsGb/DAYAmJjls02HvYbI31k8x69xK\nRqGN0VBn9z3R7wtL9zMGrnNMC075BMSXFORH+fg/lRs9Z5Jq+UnYVl5HVo4ybqvWuuPg5Vtd\nOn36a//pQgIAYYTETriFhIRcuHAhJibm9u3bSUlJ/A4HAJqcksnvx59+eHY57E9P1xFd6V7Y\n6l/MO/f1uJFTsl9z6q8j5WJ37rjOJiLK+Nv3QLL21DkjZLhOYWhhoVi20bFjRyp8/bqhnqoV\nQlGzlBmGYRixiRENedq3F33+cB1jYdSpjZqClKSMatuu/ewX+P37nns05It1xky1xJzqGEtd\ngk/3H1J81vZut7nLC5Nv7fecPqxPx9aK0hISMio6nXvbTF+17993+XU9MwgCPDwh3HR0dDp2\n7Lhp0yZ+BwIAfCSm0MFkTAeTMURU9DHqN+uh27wX7XL+d0EbIiIZu1+ddX4K9Dmxqt/wz0G+\nx7ONvGf3E+U+XF5evnyDxWIR5eTkEDSs/3bPXxVWVLaZ++px8qvHN46F/BN0O3JKGz4GVuzD\nqcV2EzbfSitfPv7T67hPr+Nunf63qGecZzc+hgbfB4kdAEAzIqpqtXCK4baFDx48IipOF0T6\nz5lt/L/ffQ5s1ni544bY4MAZHfkc5I9JRL6r/fTZ00cPMtIW/3hz96/T1lxOJfr8z/It16f8\nr1+lygPcTv1uynVs60ZdTK7o/lrbkZtic4mIFHtOWbLQyaSDksjXd4+unzoYcItpzEtDg0NX\nLACA8EqPf/Su0rLDGTEx8URqamrlRboz5tmyzm0fvyjgmZLTHCdM0/T9sp9GeE0dZKCtJC3O\nkpJv3emn0Yv33kwpb94qSIj83b6HpoyEVEvdfpM3Rj/dU7m708rn+f2jG1xse7dvrabdY8Tq\nnb92Lt7xPj4+t8r1VLsP4Ta4u0pdI6mqIP7oMrvuGmWxfay8inf6wRWri7M6Uf1l568FuU0Y\n8lPvXv0s7We4777w9MKv7SpWL3x3ds34PjoKUjIq7fs4bbicXHa+5NOeTjb9u7VVV5aTYrEk\n5VR0jW1+3nTmTVl3c3l/7v77QQtsDTTkJKucpC4fJhHlPP9n9XTrHjpK0uIsSXmNruaTvI4+\nQ0MzocUOAECYvfKz6xUgO3z8aCtjvdbSBemv7xz323UkRXHw+pncTTwKY3+dvMRyZzS1XTpn\nqGS9rpgcE3k5IZ/oUXw+UdLtiHAZSSJVYzsTHVb9bkWAZVx2M7VZfy+7dLsg6em1w0+vRRyK\nOvDvwbEaRMlHnQeMCnnPISLKSrixf8ngS9qV02eFli25NzlZWSVZiFbHjlX/ST7eO31aoXxT\nrceQHmp1iaSq5MNTBjiGJtUQW17UsTNZREQkPcbT3VCi4vHiCgoVttmXF/cPffWmOA+Lvxm2\ndGi6SvzpqapERKm3I8JO3yMRCflWSkqiqZ8+JcSc9o85c/LJ8UcBQ7lPw45w6Xcgq7CFVFFe\nztdKJ6nLh/nlX3cz69V3soiIJauiJJ7x4XF0iEf00ROe56M9+khV9zn8ONBiBwAgvNpN3Lhh\nmkH2tf3rFk5zGjNlzupDL7UcV0feipiuU6GeuMVY+1Yk2sfVxZiHX/vFM7IXu79zsqOjo6Oj\n5+mvRDG+kxwdHR0dV0Zl1fNGBBgndo1zcS4lZ+JxJj4l7d2NXXYaRFT0OnTWkqNfiXNr/YLi\nRESm37ITzz4mvzj7u3bGh5rOmXN/7YIdr4iIZCyWzeldtcLVdTbcvKPrFEk1wd9av6g4q5Pu\nsyTy8bv3T08t00yvGNv7hISSVt8O3WtfT4TzNkVl/sFr92KOLTSWIiLKOrP/yKfifS1NFx+4\nHJ+Rl5Oe9C4pLf3NsRk6RMR5H7Q5NKXiSbJaDjv4IiPr65sgu5YVTlKXD5Nzd+20NXeyiFr0\n9byelPYxKTXpv+W9xImybnrN2v7Dzw+BFjsAAOEl281hwQaHBbXWK7h27OSnFsO3Tq80Sr+T\n+12Oe4USMadwjlP5ZkZGBrH0lGTLCqz80zn+9YpZ2DyKPFY8WYz6lHUeg3UZoj6/bJsfeGzx\nf0TpkZGXqcvds6+JiEh14tpVQzuIEg36Y8P0oP5bXlV7Ps7nSyvsHFZfyySS6j7/yN8uug0W\nicOwyoc8O1sSW6vxa9YM7yxKpO65flqgyf/ecgXEKe3I5c7gv0lv7p5N4wwZoiVT+2y5HU1E\nr1+/JmpFRComdr2iDu36Y+uzxJSvOflFnHfFnbDsx4/jiH7iOonx7LXj2kkSqQ8fakTHzpWf\npCzgGj7MRxFHn3OIiFip593HXCEioq+fRImI2HdPn/u4tCPXZD4/HiR2AADN2ednN56+jgv+\nbcdbXZewMYq1H1Am7dmla5cDDzxg9Zlq9CP37nz8+LH4jXabNqV5TxsdHRH6j02U+fFj9ufP\nn4tLtXR0Sh43Ztq2bUP0qurJcuOCpw6bGfYynxhlC+/II8v7yVetRESjQjnhTpULa42k6nnK\nYmvTrl1pbB06tCPiSuw02rWToDt5RPTs7t0c0q25J5Mx6K5ffHE5ObmSm8otHiT4LnRsv0l/\nvy2qelDlx6xF2rVrW/xOSkqqwknq8mGWfQ4Zz66cr9xA9/nzZ6IfOrH7kX9Yhd727dtPnjx5\n/vx5fgcCAAKr8PSSfgNsZv/DDP9f2Kq+3zUM7t+1wxyXXVWaFrD7F63GCk8YqKqWpAlvXr8u\nbdp6/epV8SAzGVXVFq1atSouTXxTMvSMOC9fvqpyIs6niyss+k0Ne5lPkp2m//Xf6W9ldTxH\nUvWQshXNyxImouTk5Ap1JCztSlYazvrb0/tOpYdx8tPTKyRlIuLiJU1Cldv3HuzxLM7qNMcG\nP0jOKeRwsoJtqr8TRkxMpPqT1OXDLPscuq96zqnsgUfX6q/5w0CLnRDLyckRFRVt3749d6Go\nIP2TFjXUOuQNJPsLvyPgIi5I43s5NT1S19SkZGqv05RShXvmb7GJEZyJvB1qG5hZTRPQj6fr\niBHtVm6MJ3ofvGzl8KB5vSRehM3f9h8REcmPGDGQOqgO1vn9wSuipBB3L7u9sw3p3o6le19X\nOs3Lg+Otpv6VUEAkpj1q3dYZ2skxN4oTrBZaPQw06vJIS62RVNVx8OA27g9fE70K3XZkYfDI\n1kzyqS37HlespDBulfvWs8tic6jowRqrn94XT3fCfE18dO3kAf/bZsdjPeoyj11WVslIy/Ym\nw7q1kqSiV/tDr9bhuAo6DK79w+xqZ99+5foXRPe2L/ifTfBco5YixM5+f+fc33v/fNj/sP+E\n78uXmxtBygLgO8nKykpISLRpw/+ZLQEAmi2m53L/307ZbHqY++XyysG6K8t2iGqN2bHeXpYY\n4yVbJoaOCnnP+XJ5pXX7lUQkpqWlRhlJVN4iVXjt778Siv/WLXxzeL7N4fILdF315KF7p4aI\npJpDei3ZNO7gmNAkzruQ0bpnddSZj6++UguiCjm7qL7b8cOf7SZsvpVGqTFBbhOCuHbqmVLd\ndB8+QnvLzjccil7S2zTKQDwu+r/E7/6bsS4fJmO4fO/yMzZr7mZ9Oj7fWGWZkooCZSSnZBcR\nkaWhIP2ZyhfoigUAEHpf446tnWnbq52qvJS4hEyrdsZDZ3r/dS+t8nxlDSLJx4xhrPzTS7dT\nrvoscnYw664tx2IYxjYoszEuyl8KZhuvxx7ymGTRTVNBSkxMQla1Y7+RC3dfjf1rvCZDRKTi\nsPfK0eUjDFpLi0vIt+k9fs2pkJnqxceW9YU2TSRVqY4OunLYbbh+a2kxdk6+TB+X/VFrTapW\na22z6d8n/wV7ONv0aq8qL8USl1bW1jMe4rwyyP/nOk5oLWW66fTB+Tbd1OWLEmNvPGPMN17a\nZv3991iXD1POZPW1u8fXzhxqpNtKip2R8pVpqWMwcJTrqj0rrKvLb38oDEeg+mCER25urpSU\n1PXr1/v27dt4V8nIyFBQUIiNjTU0NKy6d8eOHW5ubjNnzuReUuzCnsYL57sJWlesmCDNsyVQ\nXbGS0vyOgIuIgP29KVBdsZazqpaxE/6aOnjq/tct+42b5jiwm4ZsUfrr+5cO7z90q/uOtNMz\n5Bo6hiQfs9ZzxfzSomYUT0z2cGV302BWTyMjhYSQ8BjzwK/HpwpYb3oTyHgQFcPqObBTSzEi\nYqc93OcyzDnsDYcYPY+7cZ4G/A5PuODDrB90xQIACDH2w3Ujp+x/32P55TOr+5ZPATtz8UrP\n0MPvRas7pCA7h1pINdifOV1W3EnxECGi6DmHw2Ma6qxC5tOJ3yyX3WdJK6m0FM9J+ZiaXURE\n1KKnm98iJCLfCx9m/QjYn8YAAPAd8v5Zv/Fufle3QO++FdcHIKkO4yaaFjfFxnn3YBh7v9ig\nudb66nISkobe905NV2aUp5+qsJTV2+0DxZhuqx4Tfd5lxlRlG1J15SsiEhG0NlZ+aNln7ITB\nPbXlitI/fvzKlmmt18/OZfPJB/+uMfnhOwa/Hz7M+kGLHQCA8Lp59mw6dZk3ukutE8teWjL6\ng/PKHef2tGV9yVftljlTb+82n9CNNtNKFrriPNi144qoxY6ZXYiKnPY9MSsfXZ98Yo79b1c1\njLqKN9p9CLuW5stCzJfxO4pmAh9m/SCxE24cDicjI+Ply5cMw2hra4uKVtvxAgDNVP6bN8lE\nvXXrsHZBXj/3Y5snqZVtu84x3TjPJyB+2uJ2RET5UT7+T+VGr52kSkSiCtqdShsAc+6smuZ5\nQdIh5ISHIZrmAAQefkyFW35+vr+/f7t27XR1dQ8cOMDvcACgaX3Hw2/dra3VuLc1p/46Ui52\n547rbCKijL99DyRrT50zouJzD5zEA5Ns/3jQedU/IeO18X0BIATwgyrcdHV1nz17Fh8f//Ll\nywkTJvA7HABoWhLa2ipEL1++rL1q2Wz9pWTsfnXWSQj0OZFN9CbI93i2kcvsfhUa/b9eWTLM\n+aj4tNB/fjeqdW14ABAISOyEm4iISIcOHXR1ddu2bYt+WIAfT29rawV6fCT8MQ8TV4n0nzPb\nOCPc50BS7M4dN8QGz5nBPV9Z4bNdjvab3phsPbF7+A+98iZvCu/4zxhpZtBWTbGFRIuWWnp9\nRy3bF5vK76jgR4DEDgBAeEnYLlncQ/zhumnu/2VU3JPzPDTkUlbNR+vOmGfLOrd9/KKAZ0pO\nc5y4ZtL9fHrO0DkX1H49fHheF0Ga/1FoFL15+Kiw3dCf3dbt8PvT6xdziZubpvQz/+NWIb8D\ng2YPD08Iq+3bty9fvpzNbpSZ5QFAWIh0czsSHDd46hqTztHjnR1Nu2lIF6W/vhd9OOTQre47\n0ybWvByUwthfJy+x3BlNbZfOGVq+Wmn8jpFjdn8wdDsyU/1DXNyHklIZdT1NuWqevk2Oibyc\nkE/0KD6fKOl2RLiMJJGqsZ2JjtClhGPHUnw8LwdKStKRI6SiUlYgYbftul35/uku9soG+qt3\nBV7z6lXdkq4ADQaJnbBKT08XERFp0QIDXwB+cCJtnfbFdB/ps8XvyME1h9+n5YnKa+gZW7rs\n2zN3bK3LTohbjLVvtdNP19XFmKsD53ls7FfKvr1uSNd1XHWH7c85PrGaterv75zsGFDaXhjj\nO8nRl4gsy5emECInT1Imr0uiJSZyJ3aViWppqROlieFLFxob/o8JKwUFBTk5OXl5eX4HAgD8\nJ9fZfrmf/fJv7O3kfpfjXv2ugmvHTn5qMXzr9DbcpUP8Mzn+37qW2pxozhzuAiv/9G/X/rEV\n5WXlFBTlpr2OCfdce0HedMusRlyDEoCIkNgBAPyYPj+78fR1XPBvO97quoSNUeR3OIJh9Ggq\ne3j4yxfatYtqWE7d1pa6di15n5dHhdUMnzv1i+rw4CwiIpbW8C1RB3/tgoHt0NiQ2AEA/IAK\nTy/pN+l4C7Vuw/8Xtqqv0A2GaySDB1PH0keD01JpbwAVFHyzsoU5DSwdwpidTV++VK3y0+/n\nrszIy0x+eevon1vmDx6Sfeb8sl4SDR42ABckdgLE19c3IiJCl2sO+by8PCL69OlT3U+SlVF7\nnSajoFx7naaUn8fvCLgI1PqaLWoditWE3j/ndwSV1LpYl1ASmxjBmcjvIASO6zTifiJNgkji\n29+Snm4VNg9FVq2i2KHfgA5EZDZkpGMPkY4jVvy2d+oll9YNFC1AdZDYCZCrV68+e/ZMt8ri\nQJwa+gIAAKChKEp+12oeFYjW/BeAbJ8+nWnfk2cviZDYQWNCYidAtLS09PX1d+/eXVaSkZER\nHBysUsOTVgAA0FBkJIl4mkOKwyEW9xTxnKIijqgoV7M8513k8Vhi9NvXYVlfgPpAYgcAIMRy\nQ+ylJkVNP5XpP4S7+LOPWau5cbOvJPkMaKALxXn36LxCJ7QgwqkZf2+0ECeeJwetMLoiw39k\n9wNyjoN7tNNoJZGT/Px6eFDYfzmdF6yaiuY6aGTN+AcUAADge0iKE5u3rlgOcbfPUYve9nYX\n9p0LOOuflJrFyKi2NTD9LXjpkkmG0g0TKMA3IbEDAAAgIiJxceIU8XQkU3GMnbjhtO1h0xom\nKIDvIkgP5gEAQOOInqPGKM+K5ip5takvwwwJKl1nIc67B8PY731wcIGNfmsZSVm1jibTfGLS\nv3nCzDvbh6qLKQ/0+Lc5rWwvwSIJcZ5eLGKa5+PTIHTQYgcAIPTys9LTKyRhX3J4WW3+8uIx\nGXO8A68FahTcD5w1fq5NodbL/XYylaux351YaOu0I3P43uuBkzs0p2nZxFnE4XWMnSgaSkAg\nILETYvn5+a9fvx40aFDxpru7u6lpzQt+A0CzlLV/tOL+qsWqVYtqxrbyOrJylCIRkdryrS77\ne6zbfzrQbnSFL4rs+zsnDJsbrb3k9LnVFsrNrJWKxappqYmacJrrhIcgdJDYCTE5ObmBAwe2\nb9+eiERERNTV1fkdEQDwheTQ9acW9+YuyTg633570veex9DConxtsY4dO1Lh69fviMrXkf0c\ntcRs5p/JQ3b/u296F8n6hCyYxFm8zmPHQYsdCAgkdsJk5cqVL1680NDQIKIrV66kp6eHh4fz\nOygA4DvR1gZmZmbcJZ8fKhB9d2InLy9fvsFisYhycnK4K8Qd25+a1X6Wi31zzOqISJzF41Ox\nDJEIWuxAICCxEyaRkZFfv37t0aMHEaWkpBTUsIghAAAXSUlJKqywTP2XL1+IFL7zNAM2RY+I\nGPLzMFM6HOVro9bsUhmWGI9dsQzhYUQQEEjshIm2traOjs7WrVuJaPv27QEBAfyOCACEg46O\nDmW8ePGJrFoVF7y9cPEFkfb3nkdCz/nQFZmpVhPtTTIPnA8crS1a+zFCRIznrlg8PAGCAv8R\nAQCaP7VRk6ykLm+YF3AzMeVTws2QXx23PuSxN1VMZ8y+K0enSRxyMhmz73l+w8bJZ+IsYvH0\nEhPHwxMgIJDYAQD8AFpP23/C2+j5apuOGu1Mfjkssyx4SReeTybSetiuS6cWtjo7daDdjgc5\ntR8gLMTEiCXOy0ucVXFJMQC+QVcsAIAQk5wYwZlYtVh5TjRnToUSETXz5YduL+cqseMsK9/o\n5H6X417hADGncI7TtysomW24/XUD74ELJHFxHsfYcTh4eAIEBP7CAAAAICIiMRaPL5Y4Mdzf\np5z31/aucrHr36WNsnQLBQ293iMWBN76zOvcxwDfAS12AAAAREQkWo/vxAoNdnln18zcEm85\n0mHuFD1lTlJsuO8O5/7Hbp+84ztI/lsnAGgQSOyamyJe1hFqLF/S+B1BRZIt+B0Bl+yv/I6A\ni1p7fkfARaVN7XWaUvIbfkcATUZcgteVJ6hiix3LavOTRL0O0iWbU38Z19lCz3XXuoMrB7ko\n1zNIgBohsQMAACAiIrF6LClWYYydqKZeB+7djLaleQeKfvcuiQiJHTQqjLEDABBiuSH2DCMz\n43Sl4s8+ZgyjNudqE0SQctVnkbODWXdtORbDMLZBmZX2F97xnzHSzKCtmmILiRYttfT6jlq2\nLza1CQLjgZgYsXh7sYip8eGJ5KtXn5N09+7tmupW4IeFFjsAAKiHD+f9gqJZPY1srFkh4TFV\n9xe9efiosN3Qn+3bqrcUy3xz69DuTVP6nXxxNcarl8B9AympkIRUyfuCfEr/VFNlaTlqIVvy\nns0mkW/P1cx5G/zzsnMcwzXuI6W+WQmgYQjcjxUAAAiTLivupHiIEFH0nMPVJXYSdtuu25Vv\nTnexVzbQX70r8JpXr4FNFmQd2U4neaWS9wX5tG8NsYu+WdlyLGmUNsCx2fQh4Rv1Pp+ZZzPz\nH1GHoPCl+s1roQ4QSEjsAACaP05S9KblXoFn7736lM2SV9Hu3Gva2pCF/SWJKM67R+cVOjuv\nW99223bs5quvEhrGDvO3bJ7XW7H04Phjy1fvOnP5bvy7lFwJlY79RszzXjvDqPTpTpHvnJlX\nVEtLnShNTBC/fo7tLn8wtqiQRERqmnY4KpTExEves9lkPrKaOpxPp+ZZjvRNGbInOmyyLgY/\nQRMQxJ8sAAD4LvlZ6enp3AVfcio8IP/W12nosgRzd++ggbpyBSmJT2+d/pxaQFS2qtj5xU6f\nF2w/+si8dVbs/gWTFlrY5t++/Fun4gamt3Hx8uaua2ZpKcsUfH56KWD9LPM49oMLM7/n+eWi\nvKycgqLctNcx4Z5rL8ibbpnVtz433EgYEWKzy9+X5W3fwuaema5K2sb5eNzVYvTuVOvdFw/N\n0GM1WJQANUFiJ6yys7MzMjIOHTpUVmJubq6sjMetAH5AWftHK+6vWqxa+oYT+++1HH2PLZ5T\n9YoLrB0mVKya38ctzGuEBhGR6bwDO+/o2Hp5HXM5OFKaiMhsaZhZWU3LYaP0s7QGbgu4P9PL\noO4hnvpFdXhwFhERS2v4lqiDv3YRxOYrljgRbytPEDEVu1k5SZG/mDv6Z9j4RR+ajqwOmg4S\nO+Hw999/Kyoqvnv3TlGxpHckPz8/NTXVzc2trM6WLVvs7Oy+cQIAaMYkh64/tbg3d0nG0fn2\n25NKt5juvXtJhG13dmXNsrMw6WeoI1d5rFf3oUM1yjakhwwzFQ26cOEWjTQjIir6cGG71+aD\n52JffMzILWBzOEX5xH7yhEMGdV9F66ffz12ZkZeZ/PLW0T+3zB88JPvM+WW9JHi52cYkxuI9\nsasw3Ul29CJzR7+nrUZ4j5V/cCz8QUmxeNuBI4xU6h8nwLchsRMC2dnZY8eOLX6fmloyS8Af\nf/zxxx9/8C8oABAcoq0NzMzMuEs+P1QgKkvsSGfe0fMsr/VBf7rsXpolotB+4NiF69e6GJeN\noiMlJSWuo0WVlRUoJSWFiIjyri4xHbwtz2aFV4BVN62W0iyRNzsdrLfn5ORxdeXWSrFDvwEd\niMhsyEjHHiIdR6z4be/USy6tebrdxsPzPHYMVRyNl3r7Wlw+0bvI38dHchXLTz+X7m9VvxgB\naobETghwOBwiun37tre3t46ODr/DAQDhI6ry0xyfyDk+RV9exV6I2P77MlfrzNZvQ+xLV2NJ\nTEwk0iutnZOYmFqW613bH/RcenzEEU+70v7EpLxPRLxPyCbbp09n2vfk2UsiAUzseFZhHjvN\n325wfqt3OAA8EMRBDgAA0DhE5XR62c/3mTfmMRUoAAAgAElEQVSAUmNjX5WXPwzdf6fsQYB3\n+4KjODIWFr2IqPhPS1klpbKUJ/d8WGRK3a/IKSpiVyx4F3k8lpj27XV5vIdGJMbi/VXzBMUA\nTQUtdgAAzd1H/zHDz+g4Deutp60inff2+t5Nl5k2syy5Fr3SzAwdMYyz0tWsdeadkJUeUaJ9\n17nbFa90amxrq+p3wHuLU6BLD8n314LmzwjPleU+e3JM5OWEfKJH8flESbcjwmUkiVSN7Ux0\nWESU4T+y+wE5x8E92mm0kshJfn49PCjsv5zOC1ZNFbTmOiJisXgbYkdUaa1YAL5BYgcA0NzJ\nGJgangwL9Ax6nZTBllHRMbD2OrlioSlXv6OR18lJ9+Z7/Py/5+li6kZjtwRtWdCl5AELuRHb\nT/guWrBlePtlWRLq3Swm+4T38TBbUX7s/Z2THQMySjZifCc5+hKRpV9a1AwFImrR297uwr5z\nAWf9k1KzGBnVtgamvwUvXTLJULqJbv57iPGc2DFosQMBgcQOAECISU6M4EysWqw8J5ozp2xL\nuvfs3Udm13ge8XajNp8atbnafQpGrgGXXblLhnHcyzes/NM5/t8+seG07WHTary24BAVJ4a3\np2IZtNiBgEBiBwAAQERErIZ6eAKAb5DYAQAAEBGRmBgRb/kZp6bFxwCaEBK75iYnm98RcJGS\n4XcEUDcv7/A7Ai49h/I7goqS3/A7gkbWyf0ud8fqD63WNcRqgK5YEAxI7AAAAIioeEkxnnA4\n6IoFAYHEDgAAgIiIRHnuisUYOxAUaDoGABB6X+OOrZ1p26udqryUuIRMq3bGQ2d6/3UvrWRm\n4CQfM4ax8k+najdrw/50Y9c8W6M2LVtISClqdOrvsPri18a4B0EgJk4s3l6simvFAvANWuwA\nAIQaO+GvqYOn7n/dst+4aW6zumnIFqW/vn/psO/knlcz007PkKtyAEupbdeuYi1F63T2xMNT\nTJxC0rqOmfmbc6fWoumv7l/68CGPSLb2Q4WQmDjPDXYYYwcCAokdAIAQYz9cN3LK/vc9ll8+\ns7qvQlnxzMUrPUMPv682eVMaF/hwXN3O/umAi3NI1lD/O4emty0dfrawviELMJ6nO+FUSexS\nrvqs2Xs+JiYm9vHbr4XDAr8en4qnyaAp4C8MAADhlffP+o1387u6BXpzZXVERCTVYdxE02pX\nd6jaFZv38sSqKeZd1OUlJVooaXY1G7/xagYRUULwnye+dJ27bnpbceKw2dWdrHkRY5GYOC+v\nql2xH877BUW/ZXW0se7egk93Az8mJHYAAMLr5tmz6dRl1OguvA/wKny6w8bY1itKZMiyHYf+\nOeq/7pd+nISETCLKuXL5NkftpzZPlgztrCwhJibesp3ptG3XPvO8nKrAExUnMRYvL1FW5e/T\nLivupLy8fe7Q7tl9pfh0N/BjQlesMHn8+PHp06eDg4Or3btr164xY8Y0cUgAwE/5b94kE/XW\n1eX9FOmhS5ZczLfyu392hmZxdmjtULJG2cf374vo619zp7Qe9vv2Y8aKabf2rfRaYHEn9fot\nL8N6rNEguFgs4vCUIjNVumJFMGEx8AcSO2Gyb9++xMREeXn5avf26dOnieMBAD6rf9sZ+/Kp\ns1mSI12dNasmNGw2mygrR3/rqYPz2xIRWdn0Fn/d+bdN648t+2t0c2yHEmXxPmsJpjsBwYDE\nTpj06dMH2RsAlJPQ1lYhevnyJVFn3s7w9dOnXFLX1KyueUlJSYmIOg4Z0rasqP1Qm46/XY+N\nfUKje/J2QYHWQrY8P+MQFeTWVFlMvHwZMQ4Ru6hxYwOoGzQVAwAIr97W1gr0+Ej4Y17b7mRb\ntZKk94mJ1T0ZIW9goF3SbleGzWY3425GDqfCq+YHJirVx3QnIBjwHxEAQHhJ2C5Z3EP84bpp\n7v9lVNyT8zw05FJWrScQGWgzWDr32I69idXs7DNqlCY9O3H8WWkBJy7y+HOS69uXx/ZBAcch\nUTZbpOTFEWFzRGt5cVWm5prsgrBBVywAgBAT6eZ2JDhu8NQ1Jp2jxzs7mnbTkC5Kf30v+nDI\noVvdd6ZNNK3tBArjNmwI7DfbpY/VEzdn806t2J+f3zzxqNN634kaJNLfbatT2JgV1nZflk/q\npZh2K3j1htvSA7ctHyrRFPfW5IoKeD+WEcEoOxAISOwAAISaSFunfTHdR/ps8TtycM3h92l5\novIaesaWLvv2zB1bddmJqsT0XE/e1FznsfHgqpl/pnNkVXW6mzrblKwsoTI6+OrRjktXBy+d\ntCFLQrWL6dx9a7wmdWymjVPsQuLw2qctKkZUt8U8ABoVEjsAAKEn19l+uZ/98m/sVZsTzZnz\nzU0ikmw/wvPACM9qDxZva7fyb7uVDROngCssIOJtGmaG2JKV8rrkmMjLCflEj+LziZJuR4TL\nSBKpGtuZ6DTLmWJAYCCxAwAAICJiFxCH5/U1iip9o97fOdkxoHTgY4zvJEdfIrL0S4uaoVD1\nYIAGg8SuuWndht8RcJESsHXCxQTpD+X6jOZpcJkZtddpMs9v8DuCiuRb8TsCaCpF+TzODMhw\nqvbhWvmnc/zrHxPAd0JiBwAAQERUVMjjnM8c4n1wHkDDQmIHAABARFRUwGN+xiCxA4HRTB9t\nAgD4MeSG2DPlxKSVtTubjPc6/KT2Gex4leRjxjBW/uml2ylXfRY5O5h115ZjMQxjG5TZaFdu\ndEX5VFTA44v3wXkADQotdgAAwk5y8MpDc3sScQoyP8ZF7d7kMfr0vYNxh8epNMXFP5z3C4pm\n9TSysWaFhMc0xRUbDe8tdpjBDgQGEjsAAGEnqtXb1nZIyYbTaLW3ys4Roadzx02WrFK1IDuH\nWkg15HNEXVbcSfEQIaLoOYeFPbHjdR47htBiB4ICXbEAAM2LrJISixgWq/gP9zjvHgxj7xcb\nNNdaX11OQtLQO+7Rys6M5NhDOSX1Y5bpMgzT1eNJyXbWvhHijNHahJJNzofza8Yaa8tKSspr\nGY3xOvOhUgbTjBaO5bkftqCAx6cuABocWuyEwIcPH/gdAgAItMLczMxMIirM/BgXtdHjSJ7q\nhMlDuH6/X1oy+oPzyh3n9rRlfclX7frBqrXnX1FXOY6DGKL4qKgEKSmpx+fOvV/ZWZ2o8FLU\npQLdWVZtiYgo5/oyS5v173v8sjbEoYPIy+Obp458zxB14c99NrLCejw8wS5q6GgAeILETqCJ\niooS0ZgxY4jo0aNHRkZGxeWHDh3as2ePrq5uWU0RERFXV1d9fX2+xAkAfJUV7CAbXLYloTvS\n98xuO0WuCnn93I9tnqRWuqltZSnrExV1lwYZUlpUVGyrib/Zhm+Jivoyb7Ic3Yw6/0XR1qr4\nt82n4BVbnshP+OfCLlsZIiJrm4657az8m2lixy4kNq9j7PBULAiIZtOC3jzJyMg8f/78/v37\nRNS1a9ey8vPnz9+9ezeNS0pKSnZ2Nv8iBQA+krLddOXKlStXrlw6dyxk4xTl6NmDR/g+5GpC\n6m5trcZVX8zMcqDoy6ioBKLc8+euiltauw0yF40+d7GQ6HFU1HsJc6sBIkRERVcvXilQtJ9U\nnNUREUlZThmj0WQ31sQK84nN06soDz2xICjQYifo2rdv//Xr10qFWlpaenp6f//9N19CAgAB\nI6LadcCAASUbViOGtXqvPnXxsr8m/DOhZPUqVVXVCgfIW1kZ06KoqJRFbaMu5g/YYKFomfxT\n5qqo/6hfTNRD5icXCykiIvqakpJPGpqa3MdqVtxsTtgFPLbYEWGMHQgKtNgBADQzCvr6mpRz\n796zb1fRtLTsyL4adeHauXOpPa2sFEnF0rLbh3Pn/ouKusExtLJSKq4mq6QkTikpKdyHfv78\nuTGD56eCQios4OVV/eO0X+76zbHu2lpWUlJey3D4krC4nGquCdDAkNgBADQzybduvSFSUalp\nlVt9KyvV7Av+q8697DBoUBsi6mhlpf30zB/Blwq0raw6lNQS/cnchPXh7Ol75U/CPj11OqHa\nMzYD7HwqKuTlVVh1gmLO8/8NN50Z9KHXYr/wQ74u7Z9vdxo44eA7/twY/EjQFQsAIOyK3t48\nfryQiNi5aYn3TuzYFpXXymHBxLY1HdPf0kJqR+jZz0oumwyJiMjYylJxa+BZUnQueXCCiEhl\n8spft5ptm+TadZ+nfUeRl/+snrojvkXFMyXHRF5OyCd6FJ9PlHQ7IlxGkkjV2M5EpyGny2sK\nhbzOY0dV5rHLOuqx4nL+4D2ng35WJyJb2/5i/fSWLl5zZayviWi9AwX4NiR2AADCLvesx/Cz\nRESMuJyaVttu47dsXe46SK3GYyQsrAaIhJ6TsLD6qXjZBBFTKzNW4FGR0gcnirX4af2Fk3Lz\n3ZaatHGmlu1/clx6YMVey6XcZ7q/c7JjQEbJRozvJEdfIrL0S4uaodBwt9gkCgt5nWeYqTQ4\nryjqaORXlvW0CeqlFXSnThm41PXo0f98TfrXN06AGiCxAwAQYpITIzgTa6rQyf0ux726HQrO\nZ4ucuQukxx/JH1+1nojGoBWHBq3gKpnMWcJdwco/neNf54AFWWF+Q6088erhwyxqb2DA1bip\nYmCgRhcePkyl/i3rFyZATZDYAQAAEBHp9iYJ6ZL3RQX0+FJNDXg6hiRXOoqRw670UGxKSgqR\ndssKGVzLli1LdiCxg0aExK6pxcfHe3h4VDuT8MWLF3Ny8NQUAAB/ZKdTYX7J+6ICKsqrqQEv\nJ4NES79COWxSlKhSg2GYOpUBNCQkdk3t9OnTYWFhcXFxVXfFx8dLSFT93fB95JTreYKG9EXA\nZkUoKuR3BIIqJYnfEXDBYurALy9jqKjOK4O9flD+niHqM4p7p5KSUknrXPkEgqmpqUT6LdFc\nB40LiV1TU1dXl5WVvX37dtVdS5Ysefz4cdOHBAAARFRYQGye/q5gKs9P3FZfX4bCHjzIoS5S\nJUWfHjz4SK3HdUNiB40L89gBAAix3BB7poyYhHzrTgPHeRyLz+WuE+fdg2Hs/2rAFuuUqz6L\nnB3MumvLsRiGsQ3K/O4KAqmwgIp4elXJCEUsHUbI5p8JOvihpICTEBx8iaM+cmQfPtwX/FDQ\nYidk/vzzzxs3bjx79uzDhw+11waAH4Lk4JWH5vYkTl5awo3Qzdu9HKIT/onbN0y+0S744bxf\nUDSrp5GNNSskPIaXCgKpsIDHp2I5RFSxqU/a3nPVwOPz5w9x/rJ8ZPvCByHeK28oOIQsG4BJ\n7KCRIbETMuHh4S9evGAYBo9ZAEApUa3etrZDiIho1AQzqe7dVx3cE+k7bJJsY12wy4o7KR4i\nRBQ953C1eVutFQRSQdUFJOqsckbIdPg18pLU8iXb1k8/kC7SqpPpvNCjK5006h0jQC3QFStk\ndHV1Bw8e7OLi0rlzZ37HAgACSMSgby8pKvr4MaXSjvyXR5baGrSWkZRS1B3gvP1mWvmu4r7a\nkIQT7vaG6rJS0q06D1kamcimnMch8wZ3VZWRbqljPG7T9fIjRERq+fKotYJAKiygwkJeXkXV\nDs6T7zHT9+zjpMy83C+Jd//Z4NRJqpprAjQwtNgBADQrya9e5ZBMx47qFYtjVtjc0R/vuedX\ntay7oas8frV4mn/78m+dynsG73kOX2jg8Nv/pip+it7mvmHU6PzfVY4dUfx58Q5XqVdHvVcs\nHiba/lWIvVwT305TKirk8eEJqtpiB8AnSOyEVV5e3tWrV6WkSv4CZBimW7du4uLi/I0KAPii\nMDczM7N4jF3I4lUXlcz/t2xYpd8G7xSn3P/nj24MEQ2yMVdO0XX28jrmcnBk6YS8lNRm9tMj\nLtpERPZ9s29oLd7mM+Hoi2B7BSKiEdpvLvb3DTkZZO/UjL828huwKxaAT5rxT2gz9+jRIxMT\nE+6Sffv2TZo0iV/xAAD/ZAU7yAaXbkh2W3T22LzOlQfpdx83oVvZ3Liq4ydazTh54cItGmlW\nWmbk4KBd+l5TX1+BYswdbEtXexUxMOhKRa9fvyNq00g3IQAK65HYsZHYgWBAYiesWrRoMXny\n5LVr1xZvMgyjoCBsC24DQMOQst10dmkfKsh6f//wxj/8No+caHDv2OSKfbFqampcWxKtWysW\nT6BbRlmZa3pzCQkJkldSEqtQQM39oa0CXteKJSJ2nWc2BmhUSOyEmISEhKKiIr+jAAC+E1Ht\nOmDAACIic2sbPU5XG/+FSyLsQuy55ztJSkoiale6lffhQ1rx8ghQrrAeY+wABIQwPrcEAADf\nIjtk/SYHhZTQFVseVchR7oUeeFTWGvXxYEgUW8bColfTxyfICgp4f2GMHQgItNgBADQvLR3X\nLt0YuWybx9+/hjuVLWClnhY8bHiB56yBapn3Dq764yT1XeduJ13TeWqSHBN5OSGf6FF8PlHS\n7YhwGUkiVWM7Ex1WHSsIooJ8HofKMVjjGAQGEjsAgGaG0ft1w3QfC7+Vm+6NWdO9pGPG2Ovk\nxPvzPWdsfZ4upm40Zsv5LQu68L4Kwv2dkx0DMko2YnwnOfoSkaVfWtQMhTpWEER5PK8Vy+Dh\nCRAUSOwAAISY5MQIzsQqpVLmuxM5u0u3Ornf5bgTEdGp0ZurO0l5hVJmPkkcH+4CsYrXsfJP\n5/jXFFetFQRRYQGP+RmHg8QOBAUSOwAAAKJ6tNgR4akLEBR4eEIoff78OSsr69mzZ/wOBACg\n+cgvoDxeX7UndilXfRY5O5h115ZjMQxjG5TZFLcEPx602AkldXV1Dofz8ePHqrtS3jV9ON8k\nJmALYaR/5ncEXBSUa6/TZNTb8jsCLgV5/I6gIrTE/DjyC6iIp+noGKYO/08+nPcLimb1NLKx\nZoWEx/ByGYA6QGInlBYvXnzjxg1NTU1+BwIA0Hzk5vOa2NVlSbEuK+6keIgQUfScw0jsoNEg\nsQMAACAiys1vzDF2IiIY/ARNAP/NAACEWG6IPcPIzDhdqfizjxnDqM25Wrqd5GPGMFb+6U0c\nnZDJyafsPF5eOflUhC57EAxosQMAACAiMjYl+dJV1nJzKCqipsqG/UmjTcn7okJCXgcCAokd\nAAAAEdEgB1LVKHmfk03RJ6iw4JuVTaypq2HJ+8JCys/n2leU+/VrbuloPRFJWTlJ3ueCBvg+\nSOyEAMMwRGRsbFy8qaamxtdwAKA5yHt5YsPKTaHnYl+mFEi3aqs/cKr3zsUD5ImTFL1puVfg\n2XuvPmWz5FW0O/eatjZkYX9JfsfbFNYuopzsulbe7lFhc88/XBsPvA0NV8eXbLRZeuvVOuMG\nCA+gLpDYCQEZGZnQ0FAlJSWGYVavXi0vL8/viABAsORnpadXGD/3JaewpvqFT3fY9Jt9Rcpi\n7rId5nrKhclPb56IS8ikAfJvfZ2GLkswd/cOGqgrV5CS+PTW6c+pBUQ/RGLXYDrMDLsyJKdk\nQ1KrE1+DgR8MEjvh4OTkVPzmwIEDxW9evHhx9erVf//9t6zO2rVrBw0axIfgAIDPsvaPVtxf\ntVj1W/XTQ5csuZhv5Xf/7AxNhoiIrB2K1wvjxP57LUffY4vnVD0q2TGh4eMVVBJS39FiV/XY\nctLaRgO0GyIigO+GxE5YzZ8//+HDhyoqKsWbIiIienp6/A0JAPhEcuj6U4t7c5dkHJ1vvz3p\nG9XZl0+dzZIc6epcktVxYbr37iURtt3ZlTXLzsKkn6GO3I80OCzoHGV/5eVAMXFqVfsYmeSY\nyMsJ+USP4vOJkm5HhMtIEqka25nosHi5KEC1kNgJq2nTpvE7BAAQEKKtDczMzLhLPj9UIPpW\nYvf106dcUtfUrG6+K515R8+zvNYH/emye2mWiEL7gWMXrl/rYqzY4DELInlFkm/EO72/c7Jj\nQEbJRozvJEdfIrL0S4uaodB4F4UfDuaxAwD4wci2aiVJ7xMTq52hQ1Tlpzk+kbffZqQl3Dzk\n0Tcp2NV6bgSv/ZPAzco/nVMFsjpoYEjsAAB+MCIDbQZL5x7bsTexhkqicjq97Of7zBtAqbGx\nr5oqNACoJ3TFAgD8aBTGbdgQ2G+2Sx+rJ27O5p1asT8/v3niUaf1vhPF/McMP6PjNKy3nraK\ndN7b63s3XWbazLLswO+IAaCOkNgBAPxwxPRcT97UXOex8eCqmX+mc2RVdbqbOtvIEokamBqe\nDAv0DHqdlMGWUdExsPY6uWKhKQb3AwgLJHYAAEJMcmIEZ2LVYuU50Zw5XNtqlbaJJNuP8Dww\nwrPygb1n7z4yu4FjBICmgzF2AAAAAM0EEjsAAACAZgJdsc2Nggq/I+AiLmCrECW/5XcEXHib\nB7WRxD/mdwRc+gjY+ikZn/gdAQBAnaHFDgAAAKCZQGIHACDEckPsGYZhJPpte8ldnLRtAMN0\n84z79oFJPmYMY+WfXucrpVz1WeTsYNZdW47FMIxtUCbPMQNA40FiBwAg/PJvrHY/8uV7jmAp\nte3atW3Lui8F++G8X1D0W1ZHG+vuLb47PgBoIkjsAACEncqgIT3T/vp9452iutQuyM4pIFIa\nF/jwod9I2TpfpMuKOykvb587tHt2XymeIwWARobEDgBA2DFdFqydrBa31W1vUnW747x7MIy9\nX2zQXGt9dTkJSUPvuCpdscV1dt3YOcNMr1ULCUlF3QHO22+mcZ1FRARfGACCDz+nAADCr8Vg\nrz8si856el3I+UaNS0tG7xSfuOPcg/gn4dO1q69zfrHTAfWFRx99THoSMV85aqGF7aa4OjUC\nAoCgwHQnQiY9PT05OXnPnj1Vd9na2qqrqzd9SAAgCDRnrJ+7pdfWpf9bcNOtA1N1f14/92Ob\nJ6mVbVeXAOb3cQvzGqFBRGQ678DOOzq2Xl7HXA6OlG6soAGgoSGxEzLi4uJv376tNrHT0tJC\nYgfw4xIzWrba0W/MevfwmWGOVXd3t7ZWq1paqc7QoRplG9JDhpmKBl24cItGmjVknADQmJDY\nCZmwsDB+hwAAAkrRcbVbr6PLfl+72GFRlZ2qqqq1nkBJSYlrS1RZWYFSUlIaMEIAaGwYYwcA\n0Gy0n7d+hvpzHzc/3lZZSUxM5NrKSUxMrZTrAYCgQ2IHANB8SJl7eFqLnvfyOJvFw9EPQ/ff\nYZduvNsXHMWRsbDo1YDhAUBjQ1csAEBzojpt3YLNPb1PJRF1/d5jNTNDRwzjrHQ1a515J2Sl\nR5Ro33XudmVPTiTHRF5OyCd6FJ9PlHQ7IlxGkkjV2M5Eh9WwtwAAvENiBwDQrIj2WLJm3K6R\nB//P3p0H1Jj9fwD/PG333vZV0UoUpcUSobSSFIpCdtmNZaxZf4rsW5aYUQgJo2TfKSTGaOzk\na5SIFq2S9u7vjxY3ItruvXm//uo5zznn+Twzun3uOec5T9rPN+20/OzIB78vm7DlRZZYi05D\nNgVtmmXw+dUUD3eOct+dXX4Q4z/S3Z+I7AIyL4+Xr5fAAaAeILEDABBi7BHHuSO+KJNxPfie\ne/Dzcdsl97lLvmyoNi2SO+3LQgndQRvPDdpY/aXsA7O4gXUKFgAaHNbYAQAAADQRSOwAAAAA\nmghMxTY1Rg78joDHzRB+R1CVsiDt3/zgb35HwOPeE35HwEPXgN8R/JKqna4FAKGDETsAAACA\nJgKJHQAAAEATgcQOAEDYcTPuHVjkYW2griApwZZtptt1wPRtkYlFPDWSt1szjH1gVvWHNfb/\nLnrPiikDuhtoK0tJyqvrd+k/a+8/aaU1NwSAxobEDgBAqJW82Ofeocsov7uSDrM2Bh0+6P9/\nw3XfHJxpY2K38va3Xj8hrtTS0LCloug3Tn+p4OKqiZsi89u5TF+5Y8eaGQ6y93d4du8y/VJ2\nzU0BoHHh4QkAACFW8mDVoAlh6WbLb15a2qH8JRGDRk4Z5+jebdSSgTM7Pg90lPm6lZLH3sce\nP34RcfuNzxL121S8g2LMJI92tvpT/1gT4tNrinKdbwEA6hFG7AAAhFfBqfUbHxW19wpc0kGK\np1hUe2TAGkdOUtCqPW+ra/bVVGxp4gUft46aMmy2vLaZx6rL97fyVhDV+JzVERExWnY2baj0\n7dvkBrglAKgLJHYAAMLrzqVL2WQw0M2A+fKMkqubtUjJrUsR35qO5ZF7fa6Nk3ekpOu6gyf/\n8puoftlz0Ob/fa9BalTUC5IyMdGtfeQA0CAwFSs0uFyumJhYaek31ysHBwcPHz68MUMCAD4r\nfP06lahLq1bVnJNp1UqFSl6/fkuk9/1eUvZ5b/tPZfzly1vt2EREvZ2NivW6baFv7CjIfbNv\nwsJL3A6rlgzk1DF+AKhvSOyEBpfLLS0t3bVrV8eOHautYGho2MghAQCfcb97ksslYpivxvK+\nVBJ97WaxsufQsqyOiEjc3MNNZ8uGamunXZjhOPGUqGtQqJfRjz58AQCNBomdkNHX1+/UqRO/\nowAAwcDS0mpGFBcXR9Tuy3Mf4+PTSNRMs8YXruSkpxeSmpoab5mqqmo1Nbnvz82wG+if3mdX\n5JFRrbCUB0AA4RcTAEB4denVS46eHgt79tXYXUZ4WGSpaLdeNlLVteMlo6QkTsnJVR6ESElJ\n+bIaN+X0VGtX//e9/4w4Ol5fvG5xA0ADQWIHACC8WP3mzTESf7x2wuoHn3iKS96ETFp4Nq/5\n2MWe6jX2IdrdykIs7cSRq/kVJcV3joS9qlKHm3xykvWgPzP7BESGTmgrUV/hA0B9w1QsAIAQ\nEzVZFBbwwH784u6m0ZMnDTJvJVv47uG5vf6HYkotfc9u7lPNJnZfUR3tPX2zrd9QB+lVc5x1\nRRIubvEOL1EjEhEp/+7/KXKOjXvAc5X+vkPkHp0IfVTeTqJlz/6dmjXUnQFAbSCxAwAQaqJt\nRh+9Z3Rg/frdxzfO2pGWJyavYWA+1G/9gkk2Gj84tCbVc8PV07K/Lwqc5e7PqBjYe+4MtFhk\nv0JeXrrsfMbd6NhCorcnFw87ydNMbtylrED7er8hAKgDJHYAAMKOUew4avWhUau/XUNtWiR3\n2jcPiUQ0+3iH9fGuOHy91SqW6TisU8JNy04AACAASURBVPmIncbc29y59RoxADQQJHYCJDc3\nNykp6ejRo9We5XK5RFRYWNi4QQHAr+Bv/2mX2XZd9FtIF6U+vxa0et11uaGhY7X5HRYA/Cwk\ndgLk48ePT58+nTRp0nfqPH361N7+e1MfTy7Xd1h1oG/O7wiqen6b3xHwyMnhdwQ8Mj/wOwLg\nM0nRjMubZ2xOeJ9dICavZWwz59jKJa4q/I4KAH4aEjsBsm/fvn379n3rbGlpqaioqKmpaWOG\nBAC/BqPJIRGT+R0EANQdtjsBgPqRkapxJTWK31EAAPzSkNgBQF2k5RVV85L5kqIErAZtRNyM\newcWeVgbqCtISrBlm+l2HTB9W2RiEU+N5O3WDGMfmFX9Yc3So7bP8XS1NtGSFWcYxjnoY73G\nDwD1BokdANRBwa67r9rdef/Xx9KKktLYpPe9I1/1e13w3feYQr0pebHPvUOXUX53JR1mbQw6\nfND//4brvjk408bEbuXtapJuIiISV2ppaNhS8cff9Zp0JSAo8o24nqODiWT9hA0ADQJr7ACg\nDliLeuh0fZW+6ParnXKiuSW05nZ8TLHkbGOdaSriNb58HupByYNVgyaEpZstv3lpaYfyt4cN\nGjllnKN7t1FLBs7s+DzQsZo9ipU89j72+JnLGCy9l75MhIgip4WFxtRD3ADQMDBiBwB1IiJu\n10oturuS4of8rKL8GHHlGz2az1MR5/A7rl9Ewan1Gx8VtfcKXNKB952wotojA9Y4cpKCVu15\nW12zr6ZiSxMv+Lh11JRhs+W1zTxWXb6/tWqFypdQAIBgw68qANRJceHxF++Mb6YXKHAUxDkW\npendr7/zSS7EGqzGcefSpWwyGOhm8NX4qJKrm7VIya1LEd+ajuWRe32ujZN3pKTruoMn//Kb\nqH7Zc9Dm/zVEuADQ0DAVK2SWLVumolLN5lIiIiJz587t3Llz44cEv7QCn5uvg6UV/SyaO+W9\n18ikmWYq61MzZj1NMM/RetSGhdnYBlb4+nUqUZdWrao5J9OqlQqVvH79lkjv+72k7PPe9p/K\n+MuXt9qxiYh6OxsV63XbQgYNEDEANCwkdkJDRETEyspKW1ubxWJVW0FcXLyRQwIg1kzzlgtY\nYiwiyisrYXSaKYUry6WUiCGra3jffUCFy+USMUyN/x9Koq/dLFb2HFqW1RERiZt7uOls2VAf\nEQJA40JiJ0wiIyP5HQLAF+RZFZ8iDCMlSuWPWYqIqWKdR2NgaWk1I4qLiyNq9+W5j/HxaSRq\nptmipk5y0tMLSU1NjbdMVVW1PuMEgMaCz14AqB8KKs+tVbrxO4pfTZdeveTo6bGwZ1+N3WWE\nh0WWinbrZSNVXTteMkpK4pScnMxblpKSUp9hAkBjQWIHACC8WP3mzTESf7x2wuoHn3iKS96E\nTFp4Nq/52MWe6jX2IdrdykIs7cSRq/kVJcV3joS9aoBoAaDBYSoWAECIiZosCgt4YD9+cXfT\n6MmTBpm3ki189/DcXv9DMaWWvmc396lmE7uvqI72nr7Z1m+og/SqOc66IgkXt3iHl6hV3eMk\nNebk9fhCoicvC4mS7x4PlWYTqXYeYKmDxb0AggSJHQCAUBNtM/roPaMD69fvPr5x1o60PDF5\nDQPzoX7rF0yy0ZD4sS6kem64elr290WBs9z9GRUDe8+dgRaL7FfIy0tXVnm4c5T77uzygxj/\nke7+RGQXkHl5vHy93xEA1B4SOwAAYccodhy1+tCo1d+uoTYtkjvtm4dEIpp9vMP6eFccvt5q\nFct0HNbp84idfWAWN7D+IgaABoLEDgAA/vafdplt10W/hXRR6vNrQavXXZcbGjpWm99hAcDP\nQmIHAACSohmXN8/YnPA+u0BMXsvYZs6xlUtcq9kLHQAEHBK7pibhGb8j4BH3iN8RVKUoSDtz\nWdjzOwIe/YbzOwIe6e/4HUFVIqL8jqAxGE0OiZjM7yAAoO6w3QkAAABAE4HEDgBA6OXEnlg9\n0dlMV1WOI8GSVtHt3Hei7+EHmaU1NsyKDvT2Dr5f+GV5xr398127tGkhz5FU0NDvNmTp4Sc5\nDRI5ANQvTMUCAAi10vjDY3qPOZCg2M1j7ILJ7dVlSrISHl4L8x/VMepj5vnxst9tnBUd6OMj\nrzN3hCnPziilT9f17u71WL2/l49XZ9WS11GBq1d5mN9IexQ5Tadh7wUA6gqJHQCAECt9vGbg\n6APvTBddv7DS/POWchPn+XgfCntXu/WBD0P2xOTrLjgS7lO230l/l9aZmn0C9x6NnzavZf2E\nDQANBFOxAADCq+DU2vX3Cw0X7PU1/2KjYE4bjxFWle+JLYg7s2K0jUELOTZLUknD0HrY+qhs\nuj1Xp+W8v4kujJVhGIZhGNM1/xERiYmJEckrKVX+gZBQUpIh4nA4jXVbAFBbGLEDABBedy5e\nzCKDGW4GzHcqFT/f4djttxsc2+kLd9joKxenPr9zJjb+Iw1eHHWD1c9ylez6J/vcJIlIQkGD\niKj9qOk2fpM3T1vfYeOoTs1K30TvnLMrQXvsxmFqjXNTAFB7SOyEW3x8/J07d5SUlBiGMTc3\nl5KSqrkNADQZha9fpxJ1adXqe5WyDs2fH1FoH/Dw4niNsvzPwXVE2SkNDQUWEUdZS0dHmqdF\nq0lnb7HHD5xq33Y+ERHJdJj6141tAxQb5B4AoD4hsRNuEyZMuHLlChExDBMSEjJ06FB+RwQA\njYj7A3VKr5+7mMseONVT43ujelV6fXXEs/+ks9LD1oe4d1QteXsrZNXqoXYfD0bsc1OvS7QA\n0PCQ2Ak3ExMTKSmpEydO8DsQAOAHlpZWM6K4uDiidt+qk/P+fT610ND44SXVn8IWTDyUZH8g\nYc8IJSIisnW2kbPWmT7Zd9TAnXZYmQ0g0PArCgAgvLo4OMjT02OhT789diejosKmd4mJNW9q\nVy7u/v0P1NLMTOlzkUbnzmqU/vhxUp2CBYCGh8QOAEB4sZznzzOVeLxm7JK/s6ueyXtxKPha\nLhGJ9HTsLZV/YseexOras1hEeXl5vGVqLVowFHfrVmplCTcuKjqJ2BoaSl91AACCBVOxAABC\nTKT9gmP7YnuPWWXZLnKYp7tVe3WpkqyEB5FhwUf/MdmZOcKKSN5j3bq93X6b0tX+2QJPm7Yq\npWkv7px50nat/wh1UjMyUqGgkE1hBgO0pcQkNYwM1FjKQ38fucJl/wzboa9nuXVQKXkTfWC9\n3y1R/TkznNj8vl0AqAESOwAAoSbScuj+GJOB2zcFHAtZFfYus0BUTl2/s92U/bumDyl77YSY\n/tSzdzTWLFsfsmLitiyujKqOiZWnowwREWO9eK9XnFfQ2F7rcopKTVa/uL+gNSn2D7hzpZPv\nmr37loxbnS2ipNm602+BRxeO7Yy8DkDgIbEDABB6su1cFgW4LPp2BXbr/t4H+3tXc6a505qz\nTmu+KJTQtJnxp82MeowQABoH1tgBAAAANBFI7AAAAACaCEzFNjXMj25B2hjEJPgdAfyYj1n8\njoCHSO1eXA8AABixAwAAAGgykNgBAAAANBFI7IRYcXHxixcvPn78yO9AAIBv8oNdmAoibAUN\n/U5OM3b9nVryU50kb7dmGPvAWs/Ip0dtn+Ppam2iJSvOMIxz0FcfSncX6DBfUJ4WWdvLAcC3\nYY2dENu5c+epU6dkZGT4HQgA8Be7t8/R6R2pND/j5c0DG7dPsjj3NOKRn0WjbTuXdCUgKFK8\nYydHB/Hg0JhvVBKxnH9khlnlIau1YeMEB/BrQWInxLS1tSUkJGxsbPgdCADwl6hmF2fnPkRE\n5DbMimPcafUf206ttnDnfFGv6FMeSXLE6/36BkvvpS8TIaLIaWHfTOwYrW5ubi71fm0AqAJT\nsQAATYlYxx5dOVQQH59ERLG+pgzjEvBv0HQHoxayLHYH31giIm7SlVVDOmvJsNlymp0GL7+Q\nVFqli7JWwfFnlrh0aCHDkVJp18frZGIp5T0NntHbUFVaSlGns8eGW5mVDUREfvBvSXHep4Kf\nmyUGgJ+DETsAgCYlKS4ujxhlZcWKgmvz3ZI8fXZc2tVS/EOhKlHerYV2jmvfmU5aHezaRiTu\n9MYxA98xRAZVu3ng3W+2sevcLWMU3kf6LVk3yK1wcbMTxxQmzNsxlfMq3HfpPCfR1q+CXWR/\nOK6S42Pk2dnZJaIy2mZ9xy9d69VXu/7HDgF+eUjsmgJDQ8OMjIyAgABnZ2d+xwIAfFCc//Hj\nR+LmZ7y8uXf2iusk7TjUSb7iZEG3JSc2jlSrOHz/x9JNz+SGn7r6h7M0EZGDo16+rn3gl4ld\nsvZvz49N0SIicjH/dFtznt/24eH/7XORJyLqr/U6ort/8Nkgl6E/9FdEspX9uGWdbEx0lEQz\nXkYf3rx1qVPk/UMxoUPV637vAMALiV1TUFpaamlpaWZmVnNVAGiCcve5yuwr/1lEscOIzds2\nj1KtPGvi4KD2uW5JVMSNIoVRI8uyOiIijt3oweqBW77os5Orq1bFzxpGRvIUY+PqXJEsihgb\nG1JJQsJbIu0fCdBgYmBg5UH/4cN6jjJyOjB33a0hW7oJ0p7qAE0AErumQEpKqmvXrqqqqjVX\nBYAmiOO84aJXVxJhyTfXbqnZTKrqJ3vVz4ac9PRCUtfQ4K2hUfWQiIiUlZU/H7BYLJJTUhKr\nUkB5eXm1i1eh75j+Kgd23r6dSN00a9cFAFQPiR0AgLATUTW0sLD4sboySkoS9DQ9nbcsLS2N\nSPpbLRpCcXHJTzxzAQA/DL9VAAC/EtEeNpbiSRfPP/j8JOzzc+fjG/KS3KKiqo/CJh3eeTyD\ntLt3xxI7gPqGETsAgF9Ks1E+Mzdb+42carjf20VPJO7UyjE7XkrWrc/UmJPX4wuJnrwsJEq+\nezxUmk2k2nmApY44EeXuH6y/mzPEsVMbDSWxrLhbf/25/3a65qhd87EuGKDeIbEDAPi1SPZY\ne/Ws7O8LvCy1PUmxdQ93r4NL99h51aXLhztHue/OLj+I8R/p7k9EdgGZl8fLE5GEkX0vxeBz\nf14MeJ9dIC6vadBtyo4FSyd1b1bnWwGALzFcLpffMQil/Px8Dodz69Ytc3Pzn2oYHh4+bty4\njIyMusdw8uRJd3f3Pn36vH371sPDY86cOUQUvqruHdcfAXveTVaB3xEIKnEWvyPgUVTA7wgE\nmN1kfkcAAIINa+yEXnZ2dk5OTmFhIb8DAQAAAD7DVKxwKy0tvXbtGhGdPn164cKFRFQiSK/r\nkZDgdwTwYwpquWtFg8CTkgAAtYZPUOEmKSmZmppqYmIycOBAfscCAAAAfIbETuipqKiIiWHk\nFQAAAJDYAQAIs/xgF4ZhGFY3vzje4mQ/C4Zp7x37uaT0/e0/Zjh30laUZHEU1Nt2d10ZkdMw\nIWVFB3p7B9//Yt1vetT2OZ6u1iZasuIMwzgHfWyYiwP86pDYAQAIv8LbK5cc+/Dt84lho7tY\nTtmf2HrI3PU7d6yeM8S0NCmpgZ4/zooO9PH5KrFLuhIQFPlGXM/RwaSOm+YBwHdgCg8AQNg1\n69VH4+rhxevnDVjRQbSa8+8PTvEMzu0beO/ouJYVjzTNbswAichg6b30ZSJEFDktLDSmkS8O\n8OvAiJ3wSUlJMTAwcHd3X7FiRW5uLr/DAQC+YwxmrR6lFrt5wZ7k6k7H79t25oPh9DXjWkoQ\nt7S0mhovTyzydOzUurk8R4Itr2HsODUwJrvyZKyvKcO4BMefWeLSoYUMR0qlXR+vk4mllPc0\neEZvQ1VpKUWdzh4bbmUSEdHtuTot5/1NdGGsDMMwDMOYrvmPiPBiWIBGgl804fP27dtnz55x\nOBxpaWmGEbAtgAGALyR7L/8/u5KL3suvfr11Td6N63e5aj20n83v206ZJSYmoahrNdYvOo1n\nd/o3sS/lbKau+uOvM+fCdi3qU3pmso3rrgTeTh5495v91GjqlgMH1g9XurNukNsc7yHO67Jt\n5u0I3rPYquDEPKfpxz8QUYfFUTcWmRL1XP8kPj4+Pj7+7BSdBr53AOCBqVjhw2aziWjDhg23\nb9/+999/iSg7OzsiIsLV1bVVq1b8jg4A+ENj/Nrpm8w2e22ZdWdBmyrf+FLevSuhnMPTRzd3\nWrz1RGeFzH/2+yyfZXsv49Y/yzuIExGRtdcR68r6dk6DjHI1e/rtfjhxuXFFYbL2b8+PTdEi\nInIx/3Rbc57f9uHh/+1zkSci6q/1OqK7f/DZIJehLAUNDQUWEUdZS0dHuhHuGwCqwIhdU9Ci\nRYvk5ORXr17xOxAA4B+xTgtXukvfXbsk9Is3FpaWlhLl5hmtOBeyYJijveOwhYfO+HYrebBh\n7YmK4b2SpKubpziZtW6uICPJYbOl7Hcl0/Nnz3jG9Dq5umpV/KxhZCRPYjauzvLlBSLGxoZU\nkpDwtmHvEABqhsSuKbh27drdu3dtbW35HQgA8JOC+8oFZrlHF6++W8xbrKSkRER6ffq0rCxq\n3ddRj/L+/fcZEREVRM236j33rIjT0t2nIv+OuX///qmp+lSal8fz2KyysvLnAxaLRXJKSmJV\nCigvT5DeYALwi8JULABAk9F6xtrx22y3LwgY7Py5UM7YWIsul1Z5aqK0tPTz8wzRB4JeSA07\nfsx7gHj56eSC90S6jRY2ANQbjNgBADQdHJtl3g6iV5Yvu8jzxHzXQYM06H9nTv+vooAbe/L0\nC5I1N29XdsjlkoySUkVWR/lXjpxMr30MGL4D4COM2AEANCWqY9fM2tjR91wykWF5kUj3BZuH\nHhm81GHAh0UjzRQy/9m3ct1dqZ5+i/qyiIios7OzasBB301D904xZb+LDvp9fGi+TO0jUDMy\nUqGgkE1hBgO0pcQkNYwM1FhElBpz8np8IdGTl4VEyXePh0qziVQ7D7DUEa+xSwD4URixAwBo\nUkRN56/yUK5a1sxtX1T4ArOkYK+R7sPn7Us0mb4/+uxMvfK/ALL9t57x7/9pR7/W8oq69gtu\ndtweOluv9gEw1ov3evXMDBrbq4eZmdmwoDdlxQ93jnJ3d3d39z6fQxTjP9Ld3d3d3ecy9uIE\nqFcMl8utuRZ8JT8/n8Ph3Lp1y9zc/KcahoeHjxs3LiMjo+aq3/D06VNDQ8OUlJTbt2+PHDky\nOzub92zoilp3XP8kJGqu05ik5PgdgaCqds9afsE+tt9hN5nfEQCAYMMnKAAAAEATgcQOAAAA\noInAwxNNTXbt53jrn2h1ryPnI0zFfgtmP7+jMJ/fEQAA/DB8nAMAAAA0EUjsAAAAAJoIJHYA\nAEIsP9iFYaTHn68s4L46Mb+vsYYiR5RhWi+530CX5b6L3rNiyoDuBtrKUpLy6vpd+s/a+0+a\nID1dDfCLwho7AIAm5FPYXI/1Dx02hfzRQ1lCsoV+A12m4OKqiZte2g10nT5aX5mb/G+o/w7P\n7ifunr3n3wtLWQH4CYkdAEATEv/kSR5195jZp3tDTcgUfcojSQn7jc8S9dtIlZeNmeTRzlZ/\n6h9rQnx6TVH+bnMAaFCYigUAaCJOj5Fm2nvHEh0dIsowDGO+IZEo1teUYVz2PAqZ5WjUXJot\no6ZnOXZ7TBZvu9LECz5uHTVl2Gx5bTOPVZfvb7VmGPvAijplPQT8GzTdwaiFLIvdwTeWRDU+\nZ3VERIyWnU0bKn37NrnxbhcAqoERO+HG5XIzMzPLfpaXl2cYhr/xAAAf2W14Gj94vbXTdqMd\n8dsciViKzYleEBFdnzc4e5rv3ui96kUP904eNt2xWDPuwABpIiLKvT7Xxmlzpvn0dQeddUUS\nLm7zHBRfTGRQte9r892SPH12XNrVUvxDoerX106NinpBUv1NdBv8LgHge5DYCbHXr1/n5OQo\nKiqWHe7bt2/UqFH8DQkA+IijrKXTQk6MSEpFR0eH90yp/fJjPoMUiIjUFm2ecsB0zYHzewe4\niRFRyj7vbf+pjL98easdm4iot7NRsV63LV8mdgXdlpzYOFKt+gtz3+ybsPASt8OqJQM59X9b\nAPATkNgJsWnTpllYWMjKypYdamlp8TceABBUHWxtFSoP9PT0qDgh4S2RNlFJ9LWbxcqeQ8uy\nOiIicXMPN50tG77owcTB4RtZHaVdmOE48ZSoa1Col5GAbUoO8OtBYifcTE1N+R0CAAg+OTme\nZ1XFxcWJ8vLyiIgoJz29kNTUqiRtqqpfz7VWV0ZE3PfnZtgN9E/vsyvyyKhWWLUNwHf4NQQA\n+IXJKCmJU3JylWceUlJSfqgtN+X0VGtX//e9/4w4Ol5fvEHiA4Cfg8QOAOAXJtrdykIs7cSR\nq5WvxC2+cyTsVc0NucknJ1kP+jOzT0Bk6IS2Eg0YIgD8BEzFCpMrV67MmjWrbEYkPx9vJgeA\nulMd7T19s63fUAfpVXOcdUUSLm7xDi9RIxIR+d4X/0+Rc2zcA56r9PcdIvfoROij8mKJlj37\nd2rWGGEDQPWQ2AmT2NjYly9ftmnThohERbFIGQDqgVTPDVdPy/6+KHCWuz+jYmDvuTPQYpH9\nCnl56e80yrgbHVtI9Pbk4mEneYrlxl3KCrRv6IgB4NsYLpfL7xiEUn5+PofDuXXrlrm5+U81\nDA8PHzduXEZGRi0uevjw4VmzZl25csXQ0DAlJaVZs2q+GO+eVYuOG4qgJZ+arfkdAQihQkEa\nHHf8vREu8nqrld7vecvj78zXboSrAUC9wogdAMAv7m//aZfZdl30W0gXpT6/FrR63XW5oaFj\nkdUBCCMkdk2NgiC9prG4iN8RCDCBGisvyON3BDzSf+yJzEZj1pvfETQ4SdGMy5tnbE54n10g\nJq9lbDPn2Molrir8jgoAagOJHQDAL85ockjEZH4HAQD1AtudAAAAADQRSOwAAIRYfrALw0iP\nP19ZwH11Yn5fYw1FjijDtF5yv2Gumh61fY6nq7WJlqw4wzDOQR8b5jIA8NOQ2AEANCGfwuZ6\nrH+oOyfkyq1//jk+Vb9hrpJ0JSAo8o24nqODiWTDXAEAagdr7AAAmpD4J0/yqLvHzD7dG+R7\ne9GnPJLkiBssvZe+TISIIqeFhcY0xIUAoHYwYgcA0EScHiPNtPeOJTo6RJRhGMZ8QyJRrK8p\nw7jseRQyy9GouTRbRk3Pcuz2mCyeZi9PLPJ07NS6uTxHgi2vYew4NTAmu/JkWfOAf4OmOxi1\nkGWxO/jGUk2vpQAA/sGIHQBAE2G34Wn84PXWTtuNdsRvcyRiKTYnekFEdH3e4Oxpvnuj96oX\nPdw7edh0x2LNuAMDyl8t8Sb2pZzN1FWTNZWli9KeX9u9drJNbOmjqxM/b2R3bb5bkqfPjku7\nWop/KFTly70BwI9BYies5s6d++DBg8qXT4iIiCxdutTCwoK/UQEAH3GUtXRayIkRSano6Ojw\nnim1X37MZ5ACEZHaos1TDpiuOXB+7wC3sr8A1l5HrCtr2jkNMsrV7Om3++HE5cYVhQXdlpzY\nOFKtMe4BAOoGiZ2wevXqlYiISKdOnSpLlJUFaW9iABAgHWxtFSoP9PT0qDgh4S1R2ZhcSdLV\nrcs3hlz697+U7PyiUi63pJBKnz3jkjFT3sLEwQFZHYBwQGInrJSVlQ0MDNasWcPvQABA8MnJ\nyX0+EBcXJ8rLK3/dSEHUfKvefgWOS5fvtm+vqSglLvJ6p6vD1ry8AiJ2eQtVVcy/AggJJHYA\nAL+y6ANBL6SGHT/mPUC8vCS54D2RLl+DAoDawoNNAAC/Mi6XSzJKShVZHeVfOXIynZ8BAUBd\nYMQOAOBX1tnZWTXgoO+moXunmLLfRQf9Pj40X6bGVqkxJ6/HFxI9eVlIlHz3eKg0m0i18wBL\nHfEa2wJAA0JiBwDwK5Ptv/WM/5xZm/q1XpjLatHedtT20K7LrJfW0OrhzlHuuyt2u4vxH+nu\nT0R2AZmXx8s3cLwA8F1I7AAAhBh7xHHuCJ5jU9//uL68Fdouuc9dUqWJ2NBQ7lCeY/lOU3df\nn8pbw+lzi6+bExGRfWAWN7AOYQNAA8EaOwAAAIAmAiN2dfL27du4uLifapKSklJaWtpA8QAA\nAMCvDIldLZW9KdHNzY3fgXxJgsXvCHhIy9VcpzGJCdKy7ryP/I6AR2E+vyPgIadQc53G9O4F\nvyPg0c6O3xEAgGBDYldLEhISsbGx4uI/nSlcuHBh4cKFDRESAAAA/OKQ2NWevr5+LVqpqamV\njfYBANRdfrALZ+SJ8gNRCVmVlibWQ+b4Lhygy/5uu3qSHrV91Z4rMTEx/z59k1PstDfn9Bjp\nxrguAHwDMgzh8+nTJyK6du3anTt3+B0LAAgCdm+fU6dOnTp5JHDFiFYJx5a7Wkw8k11zs3qQ\ndCUgKPKNuJ6jg4lko1wQAL4PI3bCp1WrVj169IiLi5OUxAcpABCRqGYXZ+c+REQ0aLg1x8Rk\nRciuk/5OI2veaLiuDJbeS18mQkSR08JCYxr8cgBQE4zYCR9FRcWoqChra+v27dvzOxYAEDQi\nxuZmHCpJSanyXrCCuDMrRtsYtJBjsySVNAyth62PKhvSe3likadjp9bN5TkSbHkNY8epgTGf\nx/pifU0ZxmXPo5BZjkbNpdkyanqWY7fHZPFeDStLAAQLRuwAAJqU1Fev8khaT69FZUnx8x2O\n3X67wbGdvnCHjb5ycerzO2di4z+ShRzRm9iXcjZTV03WVJYuSnt+bffayTaxpY+uTtSubH19\n3uDsab57o/eqFz3cO3nYdMdizbgDA7CSDkAwIbETbufPn09MTJSTk2MYxs7OTkFBwDaKAIBG\nUZz/8eNH4hZkxt8OnrciQslmy0IniYqTWYfmz48otA94eHG8BkNERA6ulS+rsPY6Yl3ZjZ3T\nIKNczZ5+ux9OXG5cUVhqv/yYzyAFIiK1RZunHDBdc+D83gFu+OsBIJDwqyncpkyZkpyczOFw\nGIYJCAgYOHAgvyMCgMaXu89VZl/FAbv9nIsnZrQTrTguvX7uYi574FTP8qyuqpKkq1uXbwy5\n9O9/Kdn5RaVcbkkhlT57xiXjoZbKgwAAIABJREFUitodbG0/f2PU09Oj4oSEt0Ta1XQGAHyH\n1RHCTU9Pb/bs2RkZGenp6cjqAH5VHOcNN27cuHH1/BG/CZ0lHm8cOGL/u8qTOe/f51MLDY3q\nPu4LouZb9Z57VsRp6e5TkX/H3L9//9RUfSrNyyv4XEdOjmencXFxcaK8vLyGuxcAqBOM2AEA\nCDsRVUMLCwsiIhsHR32uoWPg7PnHBwS7yBERyaiosCkqMbGUzL7K7aIPBL2QGnb8mPeAis3W\nkwveE+k2YuwAUK8wYgcA0JTI9Fm7wVU+/dDSTU/K3kot0tOxt1T+iR17Er+uzOVySUZJqfIV\nOvlXjpxM/7oaAAgNJHYAAE2Lovtqr87MY79lf2UQEZG8x7p1NhKXp3S1n7Mt5PSlSycP7Vgy\n4rfgt0TU2dlZ9e1B3023k/LyM19e3ew+PjT/5za/S405GRoaGhp67WUhUfLd46GhoaGhN14V\nNcB9AcAPQGIHANDEMPoz141T/3DMZ8ODUiIiMf2pZ++cWGxdcGrFxIFOLmPn+0dTq5YyRCTb\nf+sZ//6fdvRrLa+oa7/gZsftobP1fupaD3eOcnd3d3f3Pp9DFOM/0t3d3d3d53JuQ9wXANQM\na+wAAIQYe8Rx7oivSjk2fyZy/+St1rq/98H+3l+3l+80dff1qbwlTtwlFT+2XXL/8wEREYkN\nDeUO5S2wD8ziBtYmcABoEBixAwAAAGgiMGInrBITE9PS0lJSUhimur2pAAAA4NeDxE5Y9ezZ\n8969e18ndlkZ/IqoGpJS/I6gKlFB+vcuzuJ3BLwE6dvBpxx+RwAAILQE6Q8d/AxfX18icnBw\n6NixI79jAQAAAIGANXYAAAAATQQSOwAAYZUfOpTDsNyPfOIpe7HChGEYmbFninkK73npMkzH\nVXHf6CfW15RhXA4Xf+M0AAgPJHYAAMKKbW1jzhRGRkRzK4syIiMfSUpJfYyIuPu5XmJkZBxp\n2di04kOMANCokNgBAAgtZRub9pQWGfmkoqDwWuQtMfsp49okREa+qij8GBH5L0nZ2HT+uoOi\nT3l4SQRAU4LETmjk5+f7+PhkZWXxOxAAEBx6Njbq9DwyMqn8+O/Ia3lm1jP7Wsndj4zMLisr\nvRF5o1jU0sZSnCpmXQP+DZruYNRClsXu4Btb0Vdh3DEvZ+Pm0myOQisLz613Mhv/dgCgrpDY\nCY3ExMTY2NiSkhJ+BwIAAqSrjbUk3YmILFtm97+IiLdtrKw0elhZMFER18sWzd2PiMikjjbW\ncpWNrs132ykxYselRy+fhY7TKi+MWeo460mHWbvCw/cussg8PNPWeUMsPm8AhA0SO6HBYrGI\nSF5enrfw+fPnmzZtUlRUVFRUDAsL41NoAMA3ElY23UWKrkfe5BJRemTkYzkrK1OStrLqmBsZ\n+Q8R0ZvIyHhqZWOj/blRQbclJzaOtDTU1tAzalWR771VGH3m1Iqx/Xo5Dp23/6p/X2708uUn\n8M5XACGDfeyEW2BgYEJCgqysrIiIiJ2dHb/DAYBGp2BjY0KXIyMfUy+9a5G3RS3H9RAh0rSy\najn/SmQ8dVOKiPyXZMfY8G54aeLgoPZVRyYew9tX7lStOmyE/fizV6/+QwOtG+EmAKC+ILET\nbvb29vwOAQD4q5WNjTZtioh4RxkRkXmdZltJExF1tLKS3hgRkeWlGnGjRKynjYUoTxNVVdWv\n+1FT4032WM2bK1B6enrDxg4A9Q1TsQAAws3Mxlqa7kZG/hsZmdTKykqDiIjELKx6UHTk9TuR\nkVllNWqSnJzMc1SQlJRJSkpKDRQzADQQJHYAAMJNrKeNhWjR9dCVEU9krK0rplzlrKxMcyP3\nr498VfbobI0eHDr4pHI/vJSQ4Mul0ra2Zg0UMwA0ECR2AABCTtbGpiOlHw+/LmJh1aNyyrWl\nlZXmm2PhMWWr8GrWInOfU7+lQacvnT+8YZTtb2fJfMmSAVINGDYANAAkdgAAwk7LxqYVcbnc\nDlZWsp9LzaysJLlcrkRP6+4/8lHfefnZDfp3N4x3HTDG94b84E1XzngZiNbcDAAECsPlcmuu\nBfUnPDx83LhxGRkZP9vwzZs3WlpaKioqqamp36kWvKgOwdU3SQH7ti+H9ULfUFTI7wh4fMrh\ndwRVCdQ/G7vJ/I4AAAQbRuwAAAAAmghsd9LUfPzA7wh4cEv5HUFVAjX0IlDEJfgdAY+3CfyO\noCr8swEAIYIROwAAAIAmAokdVOO/KI2FUVH8jgIAAAB+DhI7qJSWkVPNeyELchI+Nn4sAPBj\n8oNdmOoMDS2vkBUd6O0dfP9Hn4/hvoves2LKgO4G2spSkvLq+l36z9r7T5qAraoAgG/CGjso\nx03ftSPsD1mjDYM7Dy4vKoqNuTsj7FGy5aAHjkrMd1sDAB+x7RYfmGxapUizW/kPWdGBPj7y\nOnNHmP7QSsqCi6smbnppN9B1+mh9ZW7yv6H+Ozy7n7h79p5/L7n6DhsA6h8SOyjHKC1a4NE1\n8p9Ffod2anJyC2jN5pCYfPXZIzymGcggqwMQZKI6Fm5ufeqlK3H7jc8S9dtUbFU0ZpJHO1v9\nqX+sCfHpNUW5Xq4AAA0JU7HwmZiMnb1t9Jwuim9Ss/JSYzhdbnjZzzOQ4fA7LgCopdtzdVrO\n+5vowliZshla0zX/ERFxkyPXe9oaaChJsjhyzbSNrNw2RecTEZGoxuesjoiI0bKzaUOlb98m\nV9c/AAgajNjBZwVZxy/fXnwtrWUbNYVYsii5231Fwm8u5nNM5Gt+fzgA8FFhblZWFm+BuKSc\nlARDHRZH3WD1s1wlu/7JPjdJIpJQ0CCiN/5D+y6Mt1niG9SzlWxReuLzf86nZRQRsavpOjUq\n6gVJ9TfRbZQbAYA6QmInxEaMGKGgoCAlVf7tevTo0e3atat1b9x0n7XHgpt18PPq5ZR5SyOO\nZv7Wbf3je7P+OmqeOPCRE9bYAQiu3ANuCgeqlNgFZF4eL08sBQ0NBRYRR1lLR6fyCxr335vR\neUbLNnmP0S8rcHAdXn3H3Df7Jiy8xO2waslADN0DCAUkdkLs2LFjHTp0UFdXLzvMzMysS2+M\n0szfhy+QlWQRUXlHojrtO4e3NUgpkkRWByDI2H3XnpvXhbdEQf874+yMSRcz1pGtnlPFJw+w\ntezWQUe2+nfCpl2Y4TjxlKhrUKiXEd4aCyAckNgJMUlJydmzZw8aNKie+pOXlSz/SURUikXl\nn+Nikqr4VwIg2ESbG1tbW/94fZ0Z4VfEl68N2jblT69cEfnWPYfMXrt6SmcFnirc9+dm2A30\nT++zK/LIqFZYjg0gLPDbCtVo1e25d7duNdcDAOEk2qzHtO0n777Jzoy/c3SZefK+qQ7Tj3+q\nPM1NOT3V2tX/fe8/I46O1xfnY6AA8JOQ2AEANGUsFosoLy+v2pOisjpmLr9vn2FBGf/++6qs\njJt8cpL1oD8z+wREhk5oK0ivEQaAmmGSDQBA2JW8igoNrfqKGEUjR1t9KSJSMzJSoaCQTWEG\nA7SlxCQ1jAzUsgIH97ugM9Spi75WM6mCN7f2bLjOaE+2a0NE9Clyjo17wHOV/r5D5B6dCH1U\n3p1Ey579OzVr5NsCgJ+HxA4AQNjlX1npfqVqUafVL+4uaE1EjPXivV5xXkFje63LKSo1Wf3i\n/oLmxlYdzh7Z6x2UkJxdKt1Mx9hh+dmls63EiYgy7kbHFhK9Pbl42Eme7uTGXcoKtG+8OwKA\nWkJiBwAgxNgjjnNHfL9Kc6c1Z53W8JZ0+e3PY79VX1lj7m3u3PoKDgAaHdbYAQAAADQRSOyE\nUrt27Vq0aJGRkXHr1i1+xwIAAACCAlOxQqmwsNDKyurEiRNt27b94lTep2pb8EfOB35HUJWs\nPL8j4FFYwO8IeKho8DsCHqL4WAIAqC2M2AklKSmp7t27S0pKKigo1Fz758X/reHzd1RD9AwA\nAAANB4kdVErL/Jj7dWnhx4RqSgFAUBQn3dw1o5+ZvoaiJEtaWV3X1MZ96urzb3+scVZ0oLd3\n8P3CGqolb7dmGPvArK/PlD7f0IPNMIz8+Ms/HTkA1D8kdlCOm7lr9/F2f979K7Wooqgo9v7d\n3muO94vO5PIzMgD4ttSw0R0tJwW/aePutTkoZPe6BePt1VPP7Tr54seaZ0UH+vjUnNh9S+mL\nrZ7L4hXVatkcAOodFrNAOUZh0e+uXW/eW7QjfKcGJ7eQ1uwIj8lvPnuwy7S20gy/owOAar0O\nWhuSrDL63M2gPlIVZdMXri8oKPpeq3rCjds6bnHCkAMLUgfNxNoNAMGAETv4TEzKzsoienpH\nxcS0rLy0GE6HG79bzmsrzeF3XADwLRkZGURqurpSVUoZFov3VWAFcWd8Rlrpq8qwWJLN9K3H\nb7mZTkREt+fqtJz3N9GFsTIMwzAMY7rmv7IW3KQrq4Z01pJhs+U0Ow1efiGp9OtLc+P8xy9+\n3t9/Q1/ZBro5APh5SOzgs4Ls4xcijLfcL2jZTIHTzKLkQff1ET6Psj/W3BIA+KOtpaUKPdw2\nccH+a7Fp1U6olvy3q5+Z85poObcVe4+fOOg7QOLsHFu7pf8UEnVYHHVjkSlRz/VP4uPj4+Pj\nz07RISLKu7XQznHxBZG+q4NP/LVlvOqFMQM3/++LbrkJf45f+MBxy5YBig19jwDwEzAVK8S4\nXG5KSkpcXFzZoaampri4eO17y/TxOxPcrL3f7z2dsu9qvKKZ4zuvf/po1vFT5klOj3orYDYW\nQACxnTaE+b4f47t2tPVaEpfTMupu5+gyaqqndYvyT/cPf3nNvVTiuO/GyVEtiIioT7+OosZd\n1v/fod/PjVbS0FBgEXGUtXR0pCv7fL9v6aZncsNPXf3DWZqIyMFRL1/XPpAMeK775s8J8+/1\n3PJ0aDOi/Ea7WwCoEUbshFhOTs5vv/2mW+HQoUN16Y1RmDl10OOxpk6KohVFojoGpuHzB12x\nRFYHILCULBeffp70v+tHtnlP7W9ID46snGTTznzZ7TwiIiq9fuZ8jmTf8R4tKhuIdXZ11ii4\ndu3vb3RYEhVxo0jBZaRzZarHsRs9WJ23ypvAifNvma3bObZ5A9wQANQFRuyEWGpqKpf7+XlV\nefk6br8rL1Oxmo4RlZKg8vxOjKOKfyUAgk1Mvo3l4DaWg4moJOXyXIe+fr5z/vC8OUubclJS\nPlHeXx4yx3i+nnFLCqk4Le0TkWQ1neWkpxeSukaVTas1eA/TDk+fe6WtV7SbbFZWFhEVfCom\n4hbmZmVlSUjJS9Z+3gAA6g5/soVYnTO5b9Lp/HxhA3UNAA1KVNV+9ugOfrMfPXpCpE3Sysos\nUhj4583/M/+ionTzbzwXJaOkJEFP09N5y9LS0ogqRvASHz/OLnq51ExxKW+VAy4KB2jQIW7o\n0Pq6FQCoBSR2AADCK+vlk1wNQ3UWT1F2TMxLIjU1NSIiUau+DlKHb0TEq45xrO49NSwWiygv\nL+9z2kaiPWwsxf+6eP5BaU+T8tU6z8+djyfSKa/QetzBCPu8z30Unl/osPZR3w2n53VS4V2H\nBwB8gMQOAEB4vQoYYLZbpt8wN/vO+s2lirIS7p0O+ONYukLvtRM7EhGR/LANm4O7T3Lvmjlt\npkd3vWasT+8TX8RcOl40/JpfP1FSMzJSoaCQTWEGA7SlxCQ1jAzUWM1G+czcbO03cqrhfm8X\nPZG4UyvH7HjJM2kr3bKrdUueGPJfKRGJNTextrZu1HsHgGogsQMAEF66I9avKz1+IeLAmpC3\nKZkFYvLqep3cV65dNKufTnkN0TYTTv/b0m/FhuC1U7ckfRKTV9XU62zrPMFIhIiIsV681yvO\nK2hsr3U5RaUmq1/cX9CaJHusvXpW9vcFXpbanqTYuoe718Gle+y8+HeXAPDDGN7V99AIwsPD\nx40bl5GR8bMN37x5o6WlpaKikpqaamxsPGHChOnTp39dbbNnfURZT4qL+R1BVXqCNE1UWMDv\nCHioaNRcp9E8jeF3BFXpG/M7Ah52k/kdAQAINozYCbS0tLRTp05pamoS0fv37/kdDgAAAAg0\nJHYCzdfXd/v27bKyskRUUlJCRLm5uWvXrk1MTHz9+jW/owMAAADBgsROoLVt27ZNmzbPnj2j\niqlYDodz9OjRnJychISEaptwqtuXil+kZfgdQVWZafyOgIeiCr8j4CHBqrlOo1FQ4ncEAABC\nC4mdkPn77791dXWNjY0tLS35HQsAAAAIFrxSDKrxX5TGwqgofkcBAAAAPweJHVRKy8jJ/bq0\nICfhY+PHAgA/qjjp5q4Z/cz0NRQlWdLK6rqmNu5TV59/W9vukrdbM4x9YFbFcXrU9jmertYm\nWrLiDMM4B+HzAECgIbGDctz0XTsOtdt666/kooqiotiYW719DvW7kY49cQAEVGrY6I6Wk4Lf\ntHH32hwUsnvdgvH26qnndp18UV8XSLoSEBT5RlzP0cFEkFbwAkD1sMYOyjFKixZ4dI38Z5Hf\noZ2anNwCWrM5JCZfffYIj2kGMkzN7QGAD14HrQ1JVhl97mZQH6mKsukL1xcUFH2v1c8wWHov\nfZkIEUVOCwsVsD0GAeArGLGDz8Rk7Oxto+d0UXyTmpWXGsPpcsPLfp6BzDfeFA4A/JeRkUGk\npqsrVaWUYbEkeCv98+fUPkbqcmwJScVWXdwWH/sfz/bY3KQrq4Z01pJhs+U0Ow1efiGptOoV\nRETwdwJAiOAXFj4ryDp+5rzx+rsFumoKkmoWJXe7rzjv8yALS2oABFZbS0sVerht4oL912LT\nCqurkf/PMhvLyfsTTWfuOHri4LohirfXDuo2aG/5fkl5txbaOS6+INJ3dfCJv7aMV70wZuDm\n/zXmDQBA/cJUrBB79eqVmZmZlpYWwzAiIiKrV6+2s7OrdW/cdJ+1x4KbdfDz6uWUeUsjjmb+\n1m3943uz/jpqnjjwkZMSZmMBBBDbaUOY7/sxvmtHW68lcTkto+52ji6jpnpatyj/dH+/b9Ga\nh+yBf10/4K5IROQ4wEKqc/ulC1ZeHbnLVuz9vqWbnskNP3X1D2dpIiIHR718XftAEqS37wHA\nz8CInRD78OFDWlpa37593d3dBw0apKurW5feGKWZvw9/PLmzk5JoRZGoTvvO4f83/IotsjoA\ngaVkufj086T/XT+yzXtqf0N6cGTlJJt25stu5xERUUnU1euFUgPGuClW1Bdp6zmmO6VevfqY\nqCQq4kaRgsvIsqyOiIhjN3qwOh/uAgDqCUbshJiYmBgRTZ8+vVmzZvXRn7xsxTNvIqJSLCrP\n78QkVfGvBECwicm3sRzcxnIwEZWkXJ7r0NfPd84fnjdnaVNOenohqTVvzvvlTK1FC4YepadT\n2Vl1DQ3evjSqHgKAcMGIHVSjVbfn3t268TsKAPh5oqr2s0d3oNJHj54QEckoKUlQSlIS75ZF\nye/ecUlJSan8bHp6Om8HaWmC9Oo9APhJSOwAAIRX1ssnbwuqFmXHxLwkUlNTIyIStbCzkvh4\nav+xyg2Huf8L2h9NzWxt2xOJ9rCxFE+6eP7B5ydhn587H99IsQNAA8AkGwCA8HoVMMBst0y/\nYW72nfWbSxVlJdw7HfDHsXSF3msndiQiIpVRKxf4Wy4fYzU6br67kVTK9V3e62LknPYsthUj\nomajfGZutvYbOdVwv7eLnkjcqZVjdrz8Yh/i1JiT1+MLiZ68LCRKvns8VJpNpNp5gKWOeOPf\nLwDUAIkdAIDw0h2xfl3p8QsRB9aEvE3JLBCTV9fr5L5y7aJZ/XTKa7DNfCKuN1+81H/zlMPv\niyTV29vOD129bJB22VnJHmuvnpX9fYGXpbYnKbbu4e51cOkeOy/eSzzcOcp9d3b5QYz/SHd/\nIrILyLw8Xr6x7hIAfhgSOwAA4SXT3nXWOtdZ36+k2GXyzguTd1Z/UkS919KjvZbylIzizuet\nYB+YxQ2sY5gA0Fiwxk4ocbncT58+ffjwgd+BAAAAgADBiJ1Qev369YIFC8p+zsnJqaftTgAA\nAEC4IbETSnfv3s3MzExISBg8eLCMjAzvKRlZfgVVDS635jqN6UN2zXUajZQg/Z/6KEj/ZbIy\n+B1BVc2wXy8ACA8kdkKpTZs2RCQtLV1jTQAAAPh1YI0dAIAQyw92YSqIsBU09Ds5zdj1d2pJ\n2dnk7dYMYx+Y9f0+AKDpwIgdAICwY/f2OTq9I5XmZ7y8eWDj9kkW555GPPKzYJO4UktDQzFF\n0Zq7AICmAYkdAICwE9Xs4uzch4iI3IZZcYw7rf5j26nVFu4cJY+9jz34HBwANCZMxQIANCVi\nHXt05VBBfHwSVTMVW5p4wceto6YMmy2vbeax6vL9rVUqxPqaMozLH7d3jrfWV5FksRVaWXhu\nvZPJlxsBgNpAYgcA0KQkxcXlEaOsrPj1qdzrc22cvCMlXdcdPPmX30T1y56DNv/vq1pX5g09\n2GJ2+JOU5GfHf1e+PNvWeUNsSSMEDgD1AFOxQqykpISIDhw4ICMjwzBMv379yl/7DQC/mOL8\njx8/Ejc/4+XNvbNXXCdpx6FOX7/wK2Wf97b/VMZfvrzVjk1E1NvZqFiv2xYyqFqtsOuCI8v7\nqxMRWc04uPOejvPy5SemhAyUaoQbAYA6QmInxFgslqSkpL+/f9kDcc2bN3d2duZ3UADQ+HL3\nucrsK/9ZRLHDiM3bNo9S/apWSfS1m8XKnkPLsjoiInFzDzedLRu+qGfSt+/nvfuk+jhZiQZd\nvfoPDbRugMgBoJ4hsRNienp6ubm5/I4CAPiO47zholdXEmHJN9duqdlMqvpP9pz09EL6Ylxf\nVfXrBFBJSYnnSFRZWZ7S09PrNWAAaChI7AAAhJ2IqqGFhUVNtWSUlMTpQXIykWFlWUpKCtEX\nW50nJiYS6Vcc5SUmZnyR6wGA4MLDEwAAvwbR7lYWYmknjlzNrygpvnMk7NVX9R4fOnCvtOLg\n7f59l7nStrZmjRMjANQRRuwAAH4RqqO9p2+29RvqIL1qjrOuSMLFLd7hJWpEIiJVvuNrfDzU\n34nrM9W6+cd7wT7LLouar1kyAE9OAAgHjNgBAPwqpHpuuHr6/yxz/prl7jhg8tbn3XYGeqqS\nqLx8lcnYTsvP+hn8u2mCq8vYVdFKQzZdOeNlgHdXAAgJjNgBAAgx9ojj3BHfPKs2LZI7jbdA\nRLOPd1gf74rD11utYpmOwzpV/Y4voTto47lBG+s5UgBoDEjsAAB+HX/7T7vMtuui30K6KPX5\ntaDV667LDQ0dq83vsACgviCxAwD4dUiKZlzePGNzwvvsAjF5LWObOcdWLnFV4XdUAFBvkNg1\nNc+f8TsCHlICtt66c437QfyqZKp5+xTftDGsuQ7UltHkkIjJ3z7ddsl97pLGiwYA6h0engAA\nAABoIpDYQTXePNLwexTF7ygAAADg5yCxg0pp2Z+qeUFZ0aeET40fCwD8jJzYE6snOpvpqspx\nJFjSKrqd+070Pfwgs3yb4VhfU4ZxOVz8k52mR22f4+lqbaIlK84wjHPQx3oPGwDqHRI7qPBh\n15Gr7Q4++Sut8tO/OPbpk947rvaL+cDlZ2AA8D2l8YdHdTR1WXY6w2Dogk17gg/8sXKyrcJD\n/1EdPfZ8qEvHSVcCgiLfiOs5OphI1lewANDA8PAEVJBdNM6u6z/PFh24srM5O7eI1uy/ElOo\nPNvZdpquJMPv4ACgeqWP1wwcfeCd6aLrF1aay1cWT5zn430o7F3t9hUu+pRHkhxxg6X30peJ\nEFHktLDQmHqKFwAaFkbs4DNRjp15x+gx7RSTM7PyM2PY7W54dpqnK8nhd1wA8C0Fp9auv19o\nuGCvL09WR0REnDYeI6x4H0wvjDvm5WzcXJrNUWhl4bn1TubnU2VztQH/Bk13MGohy2J38I2l\nr940BgDCAL+28Fnhx+PX7xjvfV6goajAVrQofd79zzs+zz9iYQ2AwLpz8WIWGQxyM6hxWD1m\nqeOsJx1m7QoP37vIIvPwTFvnDbElvBWuzXfbKTFix6VHL5+FjtNquJABoCFhKlZoFBYWElHr\n1q2rPcswzMGDBz08PGp/gQ8+e64HK7bx8+zklPNUI5FmDjVY/+K/WRcjzVN6Puopi9lYAMFT\n+Pp1KlGXVq1qrvpWYfTDU//XniGiXo42yumtPJcvPzElZGDloF5BtyUnNo5Ua8BoAaDhIbET\nGrq6ukeOHFFUrH4nWRERka5du9bpArIzR/ZaIMViEVFOWYmoThv98FY6KUUsZHUAAuknnmsy\n8RjevvI3WXXYCPvxZ69e/YcGWldWcHBAVgcg9JDYCZPBgwc3ZPfyUqzynxgRKQkqX3UtylKt\n3fprAGhwLC2tZkRxcXFE7WqoqqbGm7axmjdXoPT0dJ4iVVXVBogQABoX1thBNTQMn0817Mbv\nKACgRl0cHOTp6bHQpzWO3SUnJ/McFSQlZZKSklIDhgYA/IDEDgBAeLGc588zlXi8ZuySv7Or\nnsl7cSj4Gs+e4w8OHXxSmf2lhARfLpW2tTVrrDgBoJFgKlawWFpaRkVVeZeXqCgmQgHgm0Ta\nLzi2L7b3mFWW7SKHebpbtVeXKslKeBAZFnz0H5OdmSOsKiq2yNzn1K/Ie3JPtY8PQlb831ky\nX7NkgNT3uqbUmJPX4wuJnrwsJEq+ezxUmk2k2nmApY54g98XANQOEjvB0rx58z59+syZM6fs\n8Pjx4ydPnuRvSAAg2ERaDt0fYzJw+6aAYyGrwt5lFojKqet3tpuyf9f0IbKfq3VefnbEw9+9\nx29+kSXWotPgTVc2zTKo4Wvjw52j3HdXDATG+I909yciu4DMy+Plv9cMAPgIiZ1g4XA4MjIy\n9vb2ZYf//ffflStX+BsSAAg+2XYuiwJcFn3jbNsl97lLiIjonNvG71eowj4wixtYXyECQKPA\nGjsAAACAJgIjdk1NV0t+R8CDW8rvCODHnAzhdwQ8etrzO4KqRPH9FwCEBz6xAAAAAJoIJHYA\nAAAATQQSOwAA4fQxqA/Kby1MAAAgAElEQVTzHWq/R9XcR8O6u0Dny6iUp0VWrfPhfsA0B8Pm\nMmy2nGaHfvOPxObxnIz1NWUYl8PFjRk0gHDDGjsAAOHEsVly9Oj48oNPl5aP3vWql/eeiYbl\nJew2Nb1lrFGIWM4/MuPzRsis1oY8J7kvtvSz+j1Ge/TygLVtih/u910+tOd/JfeODVNv/EAB\nmgYkdgAAwklU28JNu+IgK+0PonetrNzcrPkYUjUYrW5ubi7Vn8sNX7b0emHvXeeDJrQgImfn\n7mLd9L3mrboxxN8SW7MD1AqmYgEAmqyyqczg+DNLXDq0kOFIqbTr43UysZTyngbP6G2oKi2l\nqNPZY8OtTJ4mBXFnfEZa6avKsFiSzfStx2+5mV6H3soU530qKPk6upLL4SdzxB3GDm9RXsC0\nGjO6J70LD/+7Sr3CuGNezsbNpdkchVYWnlvvfH0BAKiAxA4AoGl74N1v9lOjqVsOHFg/XOnO\nukFuc7yHOK/Ltpm3I3jPYquCE/Ocph//UFa15L9d/cyc10TLua3Ye/zEQd8BEmfn2Not/aew\nVr2VdXl8jDxbUorNktXpNtT3bELR51OvHj/OpdbGxpKfi5oZG6tR0uPHGTw9xCx1nPWkw6xd\n4eF7F1lkHp5p67whtpo0EQCIMBUr7FatWnXjxg0tLS0imjJliqmpKb8jAgBBk6z92/NjU7SI\niFzMP93WnOe3fXj4f/tc5ImI+mu9jujuH3z2/9m764Cm1jcO4M8YY2PUxkBCJKQsQkFFRCkL\nARVBxQRRr41xRbF+CmIXelUsGgsLDNRrgxcTCwMTERSQGhKj9/sDGCPEZDuw5/PX9p76DjZ4\n9r7nvCdkhKs4fI1csuhypV1o3JlJ1Z1oQxx7kA17bf7fkfkX3Fg/uzcAescBU1aZWBtpssi5\n7+KPbt+50v7G4yMJJ1yrT6HLyckBUJeX5w8rLy9fs4DX/Inp9vTs/7qRAGCgnbVCTkcPX9/o\nmYdHNn+jW4REFPbYtW43b958+fJlXl7e169fKyvxOyxCqDETJyf12sdqBgYMELd2cqi926uY\noWFXqExJ+QQAVbHnLxbQh04dq8rbVtzUyUGt9ObNuz+/NwDo8tfBg6tnjneyGzJs/OwNZ++f\nmNg+8+SiTbe5fOlIJFKjxPXbjMaO78Z7rjRuwgCxgmvX7v/8zwEhkYA9dq1bhw4dlJSUwsLC\nhB0EIURYCgoKdU+oVCrIsVji9RqAw+EAQEFmZjFwIsfKnOKrq7iVZVCRnV0MQP+5vTXGHOo+\nTDE84M6dNOjTAQBYLFZN75wSb53c3FwAg3q9eMrKynzPqCoqzOqNEEJNwMIOIYQQAABIKyhQ\ngTly33//M2u4REXyjxyhoqISQEysZqxIy8BAGo4lJnKgS+3usxITM0FlbDf+wi4jIwNAu/ZZ\naXp6XnVJiBBqAg7FIoQQAgAAsuXQwVK5cdeTlTo1oCbXeLz0u7jl5fXPD0k/GhCVCxrm5jWz\n1InZOg2TKbsUcji9dovk0NCbXNWRI3vzb/bkyKHnvMHbzMMRV6qkbWx6AkKoKdhjhxBCqBpj\n3JbtEebTR/XOmzNvrLleO2pxVtqbhMtR5eNv+jv+9MRyRWGj9QMlx9iZ6KqxxNnvb0fuC7uT\n02HS/sW8okxqxOo1/c/Nnz/E4+uykToViRF+PncYThFLLeodSzUv1N6xfPWM/sqFTw6v+V8M\nmG1YMRyvnECoaVjYIYQQqkHWnXbuoZb/mi0RG2ftSC8WZyh10DO1cZhm8CujOxIGAwbKR1zY\n9++BrPxSCqNDlz4z93ivnG7erm4Vku68Mzclly323zjlEFtMsZOl55HTPq4Nbjth6hsz4en8\n1VO3v2GLq5qM3nZ124IuOH0xQt9A4nK5318L/TmnT5+eMmVKbm5uk0vd3NzExcUDAwOrn+7d\nu3fHjh0vX7781t6mTp1aVlbGf/HE+W1/Nu9v4VYJO0F9ktLCTkBU1y8KOwGf/gOEnaA+MpG+\n/9rOEHYChBCx4Tl2CCGEEEJtBJG+iqIfVlpaKicnR6PRioqKFBUVhR0HIYQQQoSAhV2rVF5e\nXlpaunr16rNnz8rIyPAvqiLSLMXFhcJOUJ+cwvfXEZi8TGEn4CNDpEFqDsHeNtKM76+DEEIE\ngYVdKzZgwIC3b9+WlZV9f1WEEEIIiQA8xw4hhFqxO4s0SSSLXRkNmm/NUSaRrHZl//4Bcm7t\n+tvDycpIXZZCIpEcQprsUK3KurPX08FEQ55OlWS272TutPZ6we8fGiH087DHDiGE0LelXz0Q\ncoPSw8RuMCXiREKTq6SddOvnGpHXdfRfizw6qZDZH57eTE8vBZBpcm2EUEvCwg4hhNC3dVn5\nKGeVGADcmHOyycIu69BMj4iioQcfHZ+iJVHTtlCAARFC/HAoFiGE2jhuxo3NHjZd1Fh0qqRc\nOw0DS5dt8SXVi5L8jEmkEXvvBEy10lekU2nMjhYeO+/l8W3Mu7PrNySH/nP+a9e5G6ZoSQC3\nimBzVyIkerCwQwihti11t+vQpVclR/uFnLt8MXLfuml9Jdm55XwrXPVyPaS68PTzzIyXUfMV\nriy0cdiS9KPX13PiYh9wlftqvFw8tLMCVVxcQl7bcrJ/fDZOfY+QcOBQbOtWVlaWk5OTkJAA\nAF26dJGUlBR2IoQQwXAf/hfPMVi1bbW7fnXDYKfx9dco6+19zHdYewAAS89DAY80HXx9o2ce\nHvkj92PN/Py5EgqOznVTsV++M9qUmXc/zMd3gc2j3Nv3fbtT/vBLQQh9F/bYtW7v37+PiYkx\nNTU1NTU9deqUsOMghIiHZNSrJ/XJTo9Zm8IvPfjwtYmuOKOhQ+tuzyo1xN6SXHDt2v0f23tV\nVRVAEcdgzYXD3uPsBtiNW3rkvF+fyidbNkZz/tALQAj9BCzsWrdbt25xa40fP/77GyCE2hZx\ncXGAioqKBs3l5eUAFAoFAEDT8/TVnaNY9/6ZObSnFktB13ZGwAP+s+iAxWLxPSMrKDAgJyfn\nx45fva3ekCFavCadoXZ6wHn48Js3uUYItRws7BBCqBVTUlICSE1Nrd9amJrKBkklJVkAACC3\n6ztn15kHqfl5yfeOrzLLCJ01eG5Ucd3aaWlpfNty0tJyG9R6zZAzNFSv6bfjqaqq+v5FFwih\nFoEfPIQQasU6DBigB59PRVznK9S4aYcP3aii2gywINVblyyr2XPE/F2eFpD78OGHuvZnR8If\n8QqzT2GhV7jSNjY9fzBAb2dnNXh9/txr3tGTzpx7A7JmZp1/6QUhhH4LXjzROjx58sTMzExF\nRYVEIkHtt+NXr16ZmpoKOxpCSKgM5m2ZHDZij4NJhueMoUaqtPz3t4/6771BMvX1G6cAAJB5\ncLTjJU1X+1766u2kSlNvB22JJWnMsNWt24Va4ZFh9lyfWVYqhY8ifFZdIZttWDGcd+XEl4Qz\nscllAM/flQFkPIg6IU0DUDId3k+TAgAgZu693fXY6JWDh39dNrEnM+9+6NpND6T6+y8bShX0\njwIhhIVda1FZWVlSUuLp6Umn0wGgtLTU09NTS0vruxsihNo6eceDd64b+2wMOeI7d+vXSqq8\nhoHlovD/rZjQrXq6YGlDy+4xx4JXh6Rk5FdJt9M0HOwbs3KhJd8Vqya+MROfzF81bccbtriq\nyZhtIdsWdCHzlj4NmDQqML/mScLuiaN2A4DtgbwrUxnVbe1cQm+d1luyNnTJxE1FVKUulnPD\n1vlO1MMBIYSEAQu71qH6bBV3d3cGgwEAhYWFnp6eEhIS39sOISQCxJT6e+7p7/mNpVK9Zu87\nNbvZHUhoO2+94Ly16YUDDrK5B5sPIKE13CdyuM/3kyKEWhp+pUIIIYQQaiOwsEMIIYQQaiNw\nKLatIZG+v47IKisRdgI+UnLCTsCn0SxowpT8RtgJ6jP40ctDW6VOKx5zVwg7BELoz8EeO4QQ\nQgihNgILO4QQQgihNgILO4QQavUKX5/bPGt4H31VppSEhKScil5vhyn/C477VPYb+2THH1y9\nOuLx7+wCISRweI4dQgi1alXJxyYPdg9LYfYZPWmhh4E6g1yc+Tbh6smAaUFBz2+nbTH7xf2y\n4w/6+DA0F00wxomVEGo9sLBDCKFWrCpxvdOksPSeq/+LWWUqy2t2n7NiY9LRbffov7LP8mIO\n0CX/WESEkADhUCxCCLVepWc2bn5SbrQsiL+qq0bv5LpikmHts3fRyzzsTHRUGJISNIaaod2s\ngwn5vFWT/IxJpBEHHobMHWygKkuldfeLXKSp5XUX4NJkGRKJRCKRjDe8FdRrQgj9BuyxQwih\n1uve5cv50NVppN73VkxNeidnPWvdjA4K0uXZr24GbpxhnVSVeO0vDd4aNxe7pHv47Lm8X4vy\ntYyhNjOO6thvnezm56EudACQYKq15OtACP0hWNi1YiNGjKBSa26zLSYmtmPHjqFDhwo3EkJI\noMo+fvwC0EtTs66JW84pKq2seSImQadLiAEAWC05ZsVbx9be2aCoQ3//wKd/+fL69Er7rIje\nOlGZt1IxkwogqaCuqSndoq8BIfQnYWHXKklLS3t5eWlpaZHJdXfq7t69uxAjIYSEgNu4KXP3\nQJUF/9U80fj79ofqqycq06/t9N16+PLDt5n5JeVVXG5lGVS9fMkFw9pJzY0GD1ZuvDuEUOuC\nhR2hffr06dOnT6NHj87OzgaAsrK6iQc2bdokvFwIIWKgqqu3A/jw4QOAfk0Ta3RAnGk+QH70\nXIcteTWNpbcWWw7yL7Vb6Rs4oFsHeSmK2McAp8E7OZxSAFrNOkpKSoJ/AQihPwwLO0Lr16/f\nrVu3mExmeXk5AIiL4+8LIcSv16BBcnsORZ1+vcq75jQ7iqqBhSoAZD+TA6gt7OLDQ95IjYs6\ntXo4paYlozQLQFsIiRFCLQqviiW0QYMGXb9+fd++fatWrQIAMTH8fSGE+FEdF3sZUR6v8/B9\n8LWZ1bhcLsiwWLVVHZRcPXYm53u7plIBOBzOnwmKEBIM7AFCCKFWTMxg6enQ14PdV/XtdHG0\nm7OlgTqDXMLOeHcv5tADoHVTlgMAAFMHB6UDh/y2uQbPNKZ9jg+ZP/VEicx39qxsYKAIIYe3\nnewyXENKnK5m0EWZ2vKvByH0e7AHCCGEWjUxLdfQh0/PrBmu8Obk5r+njBvrNnv5zrMpSqP9\nb7yOXdQZAABkh+08v3tY8R5HHYa89gDv/3rsOrHwezOkkKyWBy/pnxcyeWDfnj17jgtJbfmX\nghD6bdhjhxBCrZ60nuPiAMfFzazBMJkVGDuLv8Weu6L2YacVj+ue1FGx3xBjv+GPhUQICQD2\n2CGEEEIItRHYY9fWZGcKOwEf6e+dxCPKiguEnYAPlUjnThn2FnaC+mJOCTsBH9sZwk6AECI2\nLOwELSMjo7CwcODAgU0uffDggaqqqoAjIYQQQqhtwMJO0KytrQcNGtStW7cml75//57BYAg4\nUmNvrqkFwNFtNhbCDoIQQgihn4CFnaB16tTp3Llz31qanp4uvFmIs3O+SrJkpRq0ln5NKZfV\nwHtFIkRMJREjJCdemXKh8OCQ6gbuh+gls1YevvMmPa9Ea/mjt37Gf/yY3M/xwYHh0RduPn6d\nklXB6KBnMnTmyuVuPRXwrG2EhA4/hqgGN2v/jpDOW2Mj08trm8qT7sUOWhrseD2riRtSIoSI\nqPjkorGbn2r/ffjq7fv3o2bpf3+Ln1f677q/tt0o6Txi7to9ezZ4DpZ9vMfDvNfcy/ktcTCE\n0E/BHjtUg6S47H/uva/GL9sUHKBBLyqFDRuDEkrUF3q4z+kmR/r+9gghIkh+/pwD5mPnDTFv\nke/t5cUcoEsM2PoyTV+3tnvfffrYzjb6s/ZuOOwzcKZCSxwVIfTDsMcO1RGXtR08JH5pX/mU\nDHZxRgK9b9xKO69ucpLCzoUQ+iHn3KVJ3VYnARwfQyaRSCSzLWkASX7GJNKIoMTDC+wMVKRp\nMsp6/SbvSmDzbfYuepmHnYmOCkNSgsZQM7SbdTChru+tevMDD0PmDjZQlaXSuvslAVmtrqoD\nACCp21rrQtWnTxkCe6kIoW/Awg7VKc2Nij5juPZ2qY4qU0rVovK2+cozPg9zC4WdCyH0Q2y3\nvEg+P0cDwGFPcnJycvLpv1RqlsR6jT4gOzU4/m1yQpg75excu7nRdR/s1KR3ctaz1u2NPH/h\n5P5lQ6rOz7B22p/Cv+Obi10CJCbsuZz47uWJKeqND/zl1q03IGVkpN2Srw4h9CNwKLZ1KC8v\nBwB/f39Jyab7z8TExEaPHq2hofHLh+Bm+fgeiVDu6b9yqH1erNo7mDe//+Yn9xccjjBLHZs4\nXBFHYxEiOkkFdU1VOXEAKUVNTU3+JVUDfE/5ODMBAJSXbZ8Zbrwh/GLwcJfq/wBWS45Z8da0\ntXc2KOrQ3z/w6V++hrWNpX1WRG+dqNz0UbmpodOWXuZ2X7diJHbvIyR0WNi1DrKysvLy8mfP\nniWRmi6wSCSSsbHx7xR2JMV5S6Z6y9KpAJBX3SSuadTndFejzDI6VnUItWrdbWyYvCd6enpQ\nkZLyCaD6D0Zl+rWdvlsPX374NjO/pLyKy60sg6qXL7lgWPvJNxo8+BtVHWRf8rT76yzZKeTE\nEgNyy74IhNAPwMKuddDX18/JyWnhgzBk6TWPSOJSVKj5Gy1OV8J3CUKtnJycXN0TCoUCwOFw\nqp+V3lpsOci/1G6lb+CAbh3kpShiHwOcBu/kcEoBaDVbKCkpNbVXbtYFT9uRu3OG7L9xbFJH\nPLMHISLAf9moCTr9X60XdgaEkEDEh4e8kRoXdWr1cEpNS0ZpFsB3T5fjZp6bZeOyL3fwvuvH\np+pTvrc6QkgwsLBDCCFRxuVyQYbF4lVmJVePnfnu8AA348x061EH8+0O3Dg+Bas6hAgECzuE\nEBJlpg4OSgcO+W1zDZ5pTPscHzJ/6okSmeY3Kb7xt/WoA68Uh/mNkUuMPpFY0yyh1X+YSbsW\nD4wQag4WdgghJMpkh+08v/vvBdscdZYWUVW72UzadaL3KquVzW2S+yA+qQzg05nl487wNctN\nucw+OKCF4yKEmkficvFuUQTi5uYmLi4eGBj4y3sI8fqDcX6X9He+9wsak0idCcUFwk7A59Uz\nYSfg06OvsBPUF3NK2An4bLko7AQIIWLDy5gQQgghhNoILOwQQgghhNoIPMeurcn+IuwEfLIy\nhZ2gvq/5319HYMhEmsz1xWthJ+CTT6RfEwDYjRB2AoQQ+mHYY4cQQggh1EZgYYeakHxfze/+\nLWGnQK1M5ge1Yx/wbYMQQsKEhR3iyc4rKmrcWlaU0kQrQjWyC0ubeINUlKaUCD6LSCqJGEEi\nkUgk1tSLpfUWcO8t1CKRSCSS1a7sFjx+VdadvZ4OJhrydKoks30nc6e114l0wTdCIgcLO1SD\nm7c/+EznAw8jv1TUNlUkPXk4aFO04+08nBMHfUPx/itPO//7MTK/sralMin546BTTx1fFePb\nRmAkZWTyI4PPFPM1lV8NivggI9PCUw6lnXTr1W9mWJrOmEWbA/as/3uMcVV6eun3t0MItRS8\neALVIDGXeQ7rHf9k2b7ogPaSRWWwYW90QqnywlHD5uhLk4SdDhEVfZmjYe+ktGUXnwawKEUV\nsOHCk4RyuYV9Dee0p+LbRmBkR4w2jYwIPpE3ahKzuoVzNuhorsWYSVkHg7+xTXkxB+iSv3U3\nsKxDMz0iioYefHR8ipZETdvC39khQui3YY8dqiMuZdvfPH6WsfynbDYnO0HSKG5uXy99aUlh\n50KERqbadtWOH6omn1PILitMkOgQ56Dt1Z6KbxuBkh/lMYzyb/DhzzXP2SeDTnMGe0xQ5Vsn\nyc+YRBpx4GHI3MEGqrJUWne/pNrGvXcCplrpK9KpNGZHC4+d9/LqtuJm3NjsYdNFjUWnSsq1\n0zCwdNkWXzPMnhz6z/mvXedumKIlAdyqKkG9VoRQc7Cwa2UKCwvzmsJms39/56Vfoy7fNNz1\ntFRTkSmpaFGZaL71ps+zr4W/v2fUhpVzoh6/Njz3qbSdDFNCxoKbZh792ucjB982giXlOHk0\n82ZwWDIAAKQfDrooPsxjNKvRejcXuwRITNhzOfHdyxNT1Gsar3q5HlJdePp5ZsbLqPkKVxba\nOGxJqhlbT93tOnTpVcnRfiHnLl+M3LduWl9Jdm45AABw4mIfcJX7arxcPLSzAlVcXEJe23Ky\nf3w2DsEjJEw4FNvKMBiMysrKJheFhoZOmjTpl/fMzfP552KEYld/Twt79kO1FJjn0WPzy+cL\nzpw3Sx+SOJCJw2qoKcU+555HyKr6O+rYF31U+wLzBnTenJq+4N4zs9yuicZ0fNsIDGXQ5PGq\n/YJDEr19DJJDg24wR593lIJHDVcr7bMieutEZd7zdACAst7ex3yHtQcAsPQ8FPBI08HXN3rm\n4ZFSwH34XzzHYNW21e761esPdhpfu2nm58+VUHB0rpuK/fKd0abMvPthPr4LbB7l3r7v2/23\nhngRQr8OC7tWRlxcfPv27ebm5g3axcTEunbt+jt7JjHnTXfylqFRAaCm94+s2dnwtK5eZjkN\n/z2jb6DPG2LsLUmhAkDNxbFimh3an1Ztl1lJwbeNQJEtPCbp7QgNjl81+WJwguqEHYMk4GWj\ntYwGD1Zu3Dh0aHveE6kh9pbkkGvX7sNIKyAZ9epJPbbTYxZlxnCbfn26a8rWTaxdVVUFUMQx\n2H7h8HwtAIABdr0kUjov2rIxeulRFxyLR0g4sLBrZUgkkq6uromJSQvsmyFDq3kkJiYlATV/\nv8VpSvguQd/G4J1+TxKTEq9925ApSkS6s4aIMJzs3mP99sA1pVde67md6Nvkb0BJSalxI4vF\nP2ZLVlBgQE5ODgAAaHqevkrx3Rjyz8x9S4rEGDr9xyzcuH6mKZO3ld6QIVq8TXWG2uktuv3w\n4Utw6fEHXxhC6MfhOXaoCRomrxab9BF2CtTKtFN/5ayObxth0p00uW9uiO/ejyaT3Q1+Yru0\ntDS+Z5y0tNy6Wo/cru+cXWcepObnJd87vsosI3TW4LlRxQAAcoaG6jX9djxVVVUAYmL4nwUh\nocGPH0IItRXtxy/2GuboOG+pm+7PbPbsSPgjXnn2KSz0ClfaxqZn/XXIspo9R8zf5WkBuQ8f\nfgAAgN7Ozmrw+vw53p2GuUlnzr0BWTOzzr/zIhBCvwMH2RBCqM1gDlt/ethPb6VWeGSYPddn\nlpVK4aMIn1VXyGYbVgyXAgDIPDja8ZKmq30vffV2UqWpt4O2xJI0ZthWl41i5t7bXY+NXjl4\n+NdlE3sy8+6Hrt30QKq//7Kh1D/7qhBCPw4LO4QQEnEmvjETn8xfNW3HG7a4qsmYbSHbFnSp\nPkNP2tCye8yx4NUhKRn5VdLtNA0H+8asXGhZe15lO5fQW6f1lqwNXTJxUxFVqYvl3LB1vhP1\ncCgIIeHBwg4hhFox2oQo7oRvLezml8T1q33SacVj7oqm15PQdt56wXlr4wVSvWbvOzW7mcNL\naA33iRzu88NxEUItDAs7Qvv69evatWu1tbV5LRUVFYWFOPUrQgghhJqAhR2hRUdHb968WUur\nbjaBioqKpKSkZjbJyGz5WD9MninsBPVp/NQJ5S3sXqywE/BRazy1mfCsiRJ2gvqshgg7AUII\n/TAs7AhNRUWFTCa/e/eO1yIpKWlqairESAihtqSZ8VmEUGuE57iiJnxKUtuXdEvYKWqkPFTb\n+JAoYRBCCCEiw8IO8WR/5RQ1bi3npHAEnwWy2UVNhCkrSikWfBaECKwkYgSJJD31YoPm7F1W\nJJLyHGF+Jcq5tetvDycrI3VZColEcgjBk4MREgQs7FCtgv1R8Z1Pvo7MraxtqUx69XpQ8H+O\nTwq4As7CZe8Pv9A55ElkVkVtU0VS4pNB/hcc77IFHQYh9CvSrx4IuZFK0bMbbEQXdhaERAcW\ndqiWzLLxfYM1y7ZG3rK+xy4qZ2+IvGV9v3TgoL53zWQEfTd3EmPZzKHBuiVbA2Osb2YXlWVv\nOBhjHccZ6GR315qBt5ZHqDXosvJRzvsHl4/vm20mKewsCIkOLOxQHTLN1qRbvKuu/Jd8dml+\nAlUnbpyBl6akcP4mi9Nt+/aO/8tAPj2XXZKbIGkQN8PMS1cK/0Eg9CuS/IxJpBERyedXjOiu\nKiMppdh5yJIzaVXAeRHhOairkrSUvKbp2C238+q2qEq75OPSo4MMjcbQ6Dl23ZXHO61IpAEH\n2fV2GJR4eIGdgYo0TUZZr9/kXQlsvkPiLWMREgb83KE65UVRtx8bHnlXqspg0hgWVe/MQx/7\nvC0SzpkxZQVR1/4z3Pu8VF2BKalgUfncfOd/Pi8K8DQdhJpQVsSu7yunovFaT1Y7LnxhMGtH\nePjm8ax7m5xd/l49xmFTvrXXnoig5Zal0V72c6O+Vq9aFLvI2n71DbrTpkNnIv3/an/Fw3n7\n60Y7jPUafUB2anD82+SEMHfK2bl2c6PxI4qQcOF0J61MRUXFunXrgoKCGi9auHChmZnZr++6\nwOfQvQimpv94Q/uC12qfYZ6T3ub3yQuu3zHL6pXYR7CjsVy2T8DVCIVO/jPN7L8+UfsI8yYZ\nbX6VtOD8v2YZtok2OBqLUD1F4S7M8MbNSg2eZ2jMfnVqpjoAwAiz4jsdvPx3jT/9NnQEAwBg\nmPrH6+a7I2JCRriKQ2bo6n/eKk69cmWnLQ0AYJCDQYVenx3Qpf4Oqwb4nvJxZgIAKC/bPjPc\neEP4xeDhLviPBSHhwc9fKzNkyBB5eXkajdagnUwmS0tL/9auZeaN7udNl6ACQEF1i5hmR+3T\nGh0yKyQEf47dvCn23tI0KgDUdCCQNfW7ntbWzqygYVWHUAO0oRsvePXib8k/PX/EzowGq5k4\nOanXPlYzMGBAgrWTA6OmQczQsCtUpqR8AtCojL/5X4WCh6st7y8NxWysi+aOLQ122N3Gpm4W\ncj09Paio3v7PvKNBXYsAACAASURBVCqE0C/Awq6VOXv2bIvtm0GXqHlEEpOiQPU9wIEsoURu\nsUM2E0a69j8KiSwlURtGnKaEb1mEGiGrGFpZWfG3ZD9jADQs7BQUFOqeUKlUkGOxxOs1AIfD\nAYCCnJwyUFaud0MSJaWGHYAAcnJydU8oFErt9gghocH/kqgJqnqvPISdgUfd6NUCYWdASLTI\nsFgUeJKRAdCV15aZmQnwe8MCCKGWhxdPIIQQqo9sbmkhnh197FpJbUvFvWMnPwgxEULoB2GP\nHUIIoQaU3FbP3W7j7zpYet3fDtpiKf/uWH26UvknpzD5knAmNrkM4Pm7MoCMB1EnpGkASqbD\n+2lSWi45QqIOCzuEEEINSfXfcu2c7PxlBxeM2k1S7DLAI+CgxbIBaxiMnxiMfRowaVRgfs2T\nhN0TR+0GANsDeVemMprbDCH0O0hcLt6giUDc3NzExcUDAwOrn165csXOzq68vPzH97BoSMsk\n+yXyzO+vI0i9LYWdgM+9WGEn4EOoE97XRAk7QX1XAoSdgI/tDGEd+eNOS735HN/ke4vxmleE\niAx77BBCCDV2d/ecKzTbXvqq0uVfXt0MWb8pVs71xGSs6hAiOCzsEEIINUYn517Z7rk9JSu/\nVJyhbmj996m1K5wUhZ0KIfQdWNi1NXS6sBPwyf8q7AT1/XdV2An4dFD//joCU1kl7AR89s4R\ndgIEAGAw4/B1oQ38IoR+FU53gpqQ+lTN/+ktYaeokfZCbc8LooRBCCGEiAwLO8STnV9c1Li1\nvDilWPBZIPsrp6kwnBQineWPEIGk7exPJpFI3Va/rN/Ojj+4enXE47Kf3N0Db01SAwpzbtQt\nz9hlRSINOMj+3dgIoT8LCztUK3//saudDz2PzK6obalIevF80J6rjgn5Ar90umD/ybjOka8i\ncyprWyqTkl4NOhjr+LgAr+NGqLE3wUFxVQDwPDjobr2RdXb8QR+fny/sAADE+i0+zid4at19\nKIDC0uraVUteGDccRAg1A8+xQ7Xklk2x7X0/aVn41QAValE5bAi7klCmuNDBdo42nSToMDLL\nJvXr/fDNsmOxAUoSReWw4ejNhDLWwiH952hJCjwMQoTHfRAY/AQ07O1lzp8PC7yyrvegPzEH\nMEm9j4vLiKaXscYGPxv7B46BEPqzsMeOWHJycp4+fbqxVkRERFWV4E5rJ9NtzXrEu3eWz8hj\nl+Ql0DrHeZh4adMlBRagXhhJ256G8eN05TPz2aX5CVS9uAlGXlqSwgmDELFVXAsMSwZ99w17\nPczFvhwNOl97/sSdRZpaXncBLk2WqR5ONd7wFgAgyc+YRBqx907AVCt9RTqVxuxo4bHzXl5T\nu+YUl1Y20Y5DsQgRExZ2xMJkMrOysngjHzdv3hTkDNJlhVGx9wyDk0rV5Jk0eYuqV+b77vq8\nKiwUWIB6YYqi/ntoGPG2tD2TSWNaVL01D37o86ZIOGEQIjROTOCRdFJPj8nd1CZ6DKIURAUe\nz61e0n35rbhlxgD9Nz9PTk5OTk6OmanJ2+yql+sh1YWnn2dmvIyar3BloY3DlqR6NVxllDuD\nRpeiUWU1+7j6xaT8xFTpCCEhwaFYYgkPD+d/Wn3nicarHTlyREFBgUSqNyjZq1cvWVnZXz92\nvk9QbIS8rr+HiX3Bc7U0mOfadfObNwv+vW6W2T+xv5xgB0ALfMJvR8h39J9obF+QpPYJ5jl3\n2vzu/YJr/5ll9Uk0l8HRWITq5J0IPJ0vbjtlkgYAjJkybP7FqMCIdDdPFQAqU02NSQWQVFDX\n1Gx4N7Cy3t7HfIe1BwCw9DwU8EjTwdc3eubhkVIAAPSOA6asMrE20mSRc9/FH92+c6X9jcdH\nEk64thf0y0MI/Qws7FofLpc7btw4GRkZcfF6v759+/aNGjXq1/crN2/iIG8pKhUACqpbyJq6\nnU531Mospwr+HLt5rpb1w4hpauuc1uyQWSH4MAgRWsahwJgSyaEersoAANLDPEYpnAwOCn3j\n6a3b/IZGQ4fWVWlSQ+wtySHXrt2HkVYAAF3+OniQt3DY+HH9JxnYhy/adHvMjj74EUSIwHAo\ntvWpHpw9d+5cbn2/VdUBADCqCykAIIlJSYjVXO1GpirRfm+/vxlGrH4YqhDCIERgb0MDYytk\n7EdZc9lsNpvNLu7tMlIJngQFJXxvSxaLxfeMrKDAgJycnKbXZQ51H6YIn+7cSftDsRFCLQN7\n7FAT1Lq9miXsDDyqnV5NFXYGhAjrUVDQYy7AiYkqJ+q1Z4YGxvqZ9G9uOpK0tDQA/dpnnLS0\n3Aa1Xj0VFZUAYmLYG4AQseFnFCGEWq3KuIOhr0HbI/x6PVF/m4qlHwm6wAEAKpUKwOE0MbX3\nsyPhj3hX3X8KC73Clbax6QkAANzy8vqXwqYfDYjKBQ1zczzFDiFiwx47hBBqrUouBB7+TOq5\ncekEK516CwzmDNrlfjzw1E6H8coGBooQcnjbyS7DNaTE6WoGXZRrTmhQKzwyzJ7rM8tKpfBR\nhM+qK2SzDSuGSwEAQFHYaP1AyTF2JrpqLHH2+9uR+8Lu5HSYtH9xT0G/RITQz8EeO4QQaq1O\nBh5nS9hOn6zTcAFr9HQXZvG5wKOZQLJaHrykf17I5IF9e/bsOS4klbeSiW+Mf5eH26Y5jZi8\nLp41ZtvV80u61AzdShgMGCiffGHf+sUzps1eGXCzsvfMPXEPgkco1T9Mg0vzEULChz12CCHU\nWo0/XTS+6SWSIyJyuRHVj1XsN8TYb2hiJQlt560XnLc2taTX7JBzs5s7dH5+PlD0WTI/Fxgh\n1NKwsEMIIfQz8l7fjI8NPpRI6e1ugqM+CBEMFnatzMCBA5WVlQHg06dPws6CEBJJ/623H31O\n2WRy4L7pHYSdBSHUABZ2rcz169fNzc0BoLKyqds3AhDqjJeOWsJOUN/jRGEn4FPcxFWKQiNL\npAG19mrCTiACOq14zF3xqxs7BBcWf38thJBQYDd6KyMuLr5s2TIAUFdXF3YWhBBCCBELFnao\nCR+fqm1/ekvYKRBCCCH0c7CwQzzZ+cVFjVvLi1Nw1AUh4kvb2Z9MIpG6rX5Zv50df3D16ojH\nZT+5uwfemqQGFObc+FNhEUItBc+xQ7Xy9x+N3Svdcctg/dE1LRVJL155/vs+w6T/k35yhDp5\nDyHUwJvgoLgqAHgeHHT3f5t7131pZ8cf9PFhaC6aYCzxs/sU67f4mGfdlMRUna5/JCpCqAVh\nYYdqyS2batv7ftKysKsBKtSictgQdiWhVHGho+0cbTpWdQgRGvdBYPAT0LC3lzl/Pizwyrre\ngyh/YK8k9T4uLiP+wI4QQgKDQ7GoDplua9YjfnJn+Yw8dkleAq1z3BQTL226pLBzIYSaV3Et\nMCwZ9N037PUwF/tyNOh87fkTdxZpanndBbg0WaZ6ONV4w1sAgCQ/YxJpxN47AVOt9BXpVBqz\no4XHznt5Te2aU1za9CX4kHt/36whBu3laBJ0+Y69XJafel3aMi8PIfTjsLBDdcoKo27eMwxK\nKu0gz6TJW1S+Mt971yepsFDYuRBCzeLEBB5JJ/X0mNxNbaLHIEpBVODx3Ool3ZffiltmDNB/\n8/Pk5OTk5OSYmZq8za56uR5SXXj6eWbGy6j5ClcW2jhsSapXw1VGuTNodCkaVVazj6tfTEo5\n37KS+6us+80ISzOet+d49KFNY+TvbHTu4xycIoCXixBqBhZ2rZWDg4M8HwUFhaioqN/aY75P\n4HWvTNlNU2zP9WLSKcx5Y23vDZR7fOW6WWw+9w+lRgj9eXknAk/ni9tOmaQBoDBmyjDp0guB\nEekAAEBlqqkxqQCSCuqampqampqqcnUn4JT19j7mO6xLOxmmlqXnoYCJkvG+vtG1V1DROw6Y\nsmrz7uCzF6IjdswyyDqz0r732KO8edGzQpdteEobGRwbvni8o53T1PUxV1Z3zz/vvfZahUBf\nO0KoATzHrvUhkUg7duxo164dmUzmb+/Xr99v7Vdu3qRB3lJUKgB8rW4ha+p2Ot1RK7OciufY\nIURYGYcCY0okh3q4KgMASA/zGKVwMjgo9I2nt27zGxoNHdqe90RqiL0lOeTatfsw0goAoMtf\nBw/yFg4bP67/JAP78EWbbo/Z0YcEUHnrWmyZlKu7i3ztKmKdPNzNV867du0Z2Bj/0deHEPoZ\nWNi1Sp6eni2wV4YUteaRmJiUBNRUjWSqEvmbmyCEhO1taGBshYzzKGsum80GAOjtMlIpeH9Q\nUIL3epNmt2SxWHzPyAoKDMjJyWl6XeZQ92GK4QF37qRBnw4ABTk5ZaCsosL/nU9ZVZUEid/a\nAUJIMLCwQ01Q6/ZqtrAzIIR+xKOgoMdcgBMTVU7Ua88MDYz1M+nf3NeytLQ0AP3aZ5y0tNwG\ntV49FRWVAGJi1efvyLBYEnA3PZ3LdxvDjM+fuc3tACEkCFjYEVpBQUFVVZW3tzevpby8/NOn\nT81sghASIZVxB0Nfg7ZH+MGJ/LfYzT/nNXLrkaALW/s7SFKpVAAOhwMg3WDjZ0fCHy31615d\nqn0KC73ClR5pUz1tHbe8vIpC4asK048GROWChrl59eAt2cLWUiLybNgptqMzo3qL1yFh8dDO\nw6ZbS71WhNCPwMKO0DQ0NHR0dN6/f89r4XK5RUVN3B8CISSCSi4EHv5M6rlx6QQrnXoLDOYM\n2uV+PPDUTofxygYGihByeNvJLsM1pMTpagZdlGtOulArPDLMnuszy0ql8FGEz6orZLMNK4ZL\nAQBAUdho/UDJMXYmumoscfb725H7wu7kdJi0f3HtdMWKk9Z67+7n627p9n7xKAOpzNj9qzcl\nyNkHLbfB/yoICRV+BAmtR48er1694m+h0Wh6enrCyoMQIpSTgcfZErbTJ+s0XMAaPd1lwcVj\ngUczx/9ltTx4yfslIZMHbioorzJa/+axd83qJr4xE5/MXzVtxxu2uKrJmG0h2xZ0qemkkzAY\nMFA+4sK+fw9k5ZdSGB269Jm5x3vldPN2vCPQevpcj1VZvnL39plHs8rp7bvZLD6xfpWzhkBe\nN0Lom0hcLs5k0ZrQaLTo6OjBgwd/a4VVIwUZ5ztUVYWdoL7HicJOwEdORtgJ+MgSKUx7te+v\nI0hq2sJOwMd2xp/ZT5KfceeVmkfKo1zx2z1CbQvOY4cQQggh1Ebgl7W2hvIn7hD5p+Q1dYci\nIepApB5EQp0qSagwbIK9bb7ECzsBnz/VY4cQaquwsEMIIZHTacVj7gphh0AItQAcikVNSHmk\ntvnRLWGnqPEhQW19AlHCEE3qc7V/nhPlh0OoMAghJJqwsEM82eziJgbkyopTigWfBbLZTY0O\nlhWlEGnMUFiy8zlN/BjKOcL5TREpjGiqSP9vv6djT301eTpVWqG9trH1qFnrL+J0lwiJJizs\nUA0ue/+hi51Dn0Zm8e7hXZH07OmgHRcd77EFfek0l70/NKZz0ON6YZ4+HrTtvONdgYchnK/7\nj9/ofORlZA7fD+fly0F7bzg++irwHw6hwoikLyfdevSbHpGqO2rJ9pDDgZu8pw5o/+XC/jNv\nhB0MISQUON1JK/Pd6U78xvz6ziuKr959vuy/TLoq7XEK9FUpSShtt3Bg1zk6UpK/tkPx3ziH\ns6Lo6p3EZbGZ9Pa0xx+gryonoVRp4SDDOXq/GgYAqqp+Pc8f9zvXK1Ryrj54texuNl2Z+jgN\n+iqVJpSyFlrpz+lI//UfDnHCtGv3/XUEqaxM2An4eIU1aPi4qZfGkhS3C+9DhkjVtXJLS8up\nVAmBRkMIEQL22KE64nTbvj3jp3aT/5zLLslNoHWNm97L65erut8NI2VrYRY/3UD+cw67JCeB\nZhg3q4/X71R1bQlZ0ra3cfxEffkMNruEnUDVj3Pv7iWUqo5oYURPbm4ugLK2tlS9VlL9qi73\n/r5ZQwzay9Ek6PIde7ksP/W6tHZRkp8xiTQiKPHwAjsDFWmajLJev8m7EtiCio8Q+tOwsEN1\nygqirscb7n9Rqq7AlFSwqHphvive52VBoXDCfI26estw77PaMM/Md8T5vPgqnDBEU1YYFffA\nMOxNqZo8kyZvUfXa/OADn9eFQvpNESmM6OnUr58iPP3nL++wm0nZTfYtltxfZd1vRlia8bw9\nx6MPbRojf2ejcx/n4BS+VWK9Rh+QnRoc/zY5Icydcnau3dxo/P0h1ErhUGwrQ6FQRo4cqaWl\n1aBdTEzM3d1dT0/vl4diuWyfXdcjWPr+Q/Xt85+qRcJRL0O1V68WxLx6Y2ydaM0g/cI+f3ko\nlsv28b8codDZ36Gzff5jtSNwdKmxWtLLBedevuk+MNH2l8JAmxmK/eqz/78IeW3/gTr2X1+q\nRcHRuZ3V3r5dcPndG4O+iRayv/jDIU4YHIptRqOhWICcuLVu7n7n35cAUOTUDcxt7UZMmuVh\npVrz6cvaN1Btxn2HyPcnR8kDAEBVkp9pt5WfPK5+2m8jXn0Lig+jI5OPjWJWb/BkZWfjDV2P\nc0644HRYCLVC+MFtZbS1tT9//pybm9ugnUQiDRky5HduI0tizJts5y1NowJAfnUTWVO/y2nt\njpkVNMHWCgAkxrxpjg3DdOp2WkdHCGEIR3beeBtvKSoVAL5Wt4hp6uid1tLILKcK/IdDqDCi\nidVv+blXs9/c/vfStfh7d+OuHlt7Ifif/f+7FOdjJglQeetabJmUq7uLfO36Yp083M1Xzrt2\n7RnYGFc3dbexYfL2p6enBxUpKZ8A8L6vCLVCWNi1MklJSS22b4Y0reaRGFlKAmpuBi5OUxLG\nu4RQYYiGIUWteSQmJkWp/eGQqUpkUQ8jssQZuv1G6/YbDQCVmVcWDR7q7/f3Xo//FmhAQU5O\nGSirqPBX2cqqqiRIzMnhNcjJydUtpVAoABwOR2DhEUJ/Ev6XRE3oYPhqnrAz8Kgbv/pb2BkI\nq33nV8S5xRShwogustKAhW7d/RcmJj4H0AAZFksC7qancwF4tV3G589cYLFYwoyJEGohePEE\nQgi1Xux3zz+V1m/KT0h4B6CsrAwAQLawtZQoPBt2inehK/d1SFg8tLOx6SbYpAghgcAeO4QQ\nar0+HBjeM1DGcZzLAFN9Falydsqjcwf2nsphDtr4Vw8AAFCctNZ7dz9fd0u394tHGUhlxu5f\nvSlBzj5ouQ3++UeoLcJPNkIItV7aEzZvqoq6dD18w+FPmXml4oz2eiaj1m5ctsBRs2YNWk+f\n67Eqy1fu3j7zaFY5vX03m8Un1q9yxisjEGqbcLqTtuZ37jzxx/3OnSdaQhuZ7qStw+lOmtHE\ndCcIIcQHz7FDCCGEEGojsLBDCCGEEGojcCgWIYQQQqiNwB47hBBCCKE2Ags7hBBCCKE2Ags7\nhBBCCKE2Ags7hBBCCKE2Ags7hNAfUcFOefbg9t13+cIOAkCwMAghJDhY2KE6mZGzraynHk5r\ntCDt0BQra8+T2SIbhigqH6/pr6XVe9HNwqaWFsYuMtPSslr/rFLQufLu7HA1aqegadDTfPDm\n+zWNX45OMe7We8VNQachVBgAqMh9HXfm0MGAf3b4N3D+reDTIITaPC5CNXL2DiCDyfr3TSx6\ns8YIxAcfyBWtMMedf/Rj5Hy8xcNwuVwu+5CTJNAdQr58a4UvoY50kHI5mi+QODUqXmw1kwKQ\n1rYebqYKctMv1y4oiBwpBSqzr1eJahguNzdunYMGTchvG4SQSMEeO8TzIjGxkmVqqtXEIh1T\nU0ZFYmKSaIWhyrK+R1qixVPUKTpz7ByHMXrOeMVvraE4btYoRtGZI2eKBZeKc8bP9055b7/4\np9cOuunyL5G2H2ZNTr91652IhoHso9Mcl53LN3Bfs3asHlCt/j6ww897io0GFSR0Rq0NDp/X\nS4BhEEIiAgs7xJObmwssFqvJZe3aKUJ2tgCHP4kQxjEo+9syX5xZO0ZPqgoAJNqrCeTupk8f\nPCiHvpb9m7kDr7ilpTmU3b//RBB5qiVcvZov6bTIy4DeaBG9U6cOkJbWeDhdNMJkHNp9iq3k\nEXkzeIWHuSKIaw+Y6rl8/cGrSc8jXEpPHXygaqwuuDAIIVGBhR3iYbFYkPrmTWkTi0revk0D\nBoMhomEaKH5z1s+lm07fGXtuF+uMWhP94rV/f0EcNysrC2SVlCSbW0dSSUkGsrKyBJGnWk5O\nDqhqajbZdUkmk6GgoEBEwzx98oTLcBg1UBKARCJBVVVVdTtNe/yeNXaf962NEOCvCSEkKrCw\nQzw9LCzonDPbdyaVN1hQ/nLntjMcWt++JiIahqcq+36Qp5Vu12ErT76l950RcPvts8gVw7Qb\ndw+1CBqNBpyiomZvAsgtKuKApGSzxd+fxWQyv1VJ5j169AFUVFRENExZWRkotmsHACAhIQEl\n+flltYvkjI21KhISBNixihASFVjYIR5Jp4WztcvvePftM+2fC4/eZhRyCjPePrrwz7Q+Fkvv\nlnecvchFQAUM4cIAAJQkX9wwzli795R/brI1h604mfj2VsAMs3ZkAUZQV1eH8ocPE5tb5+nD\nhxXQoUMHQWUCMOnbl/b1/MkrjTpX866t2Hi5kmFlZSSiYZSVlWtPGWCoqUlzExOf1S4q+/Ah\nXXBBEEIiRdhXbyBCKU0McGjfuFYht3cMSCwV1TCVuY9C/x7QgQoAYgo9J++88alMgEfnd2OO\nCoDKX/8WfmuFwkvTlAFU5twQZKqSW393FCOp2PnF3PTrC3LTznx5fe/i/oXWqhQAisGaJ5Wi\nGqYgbJgE9N2ezuVyuewQByrIW6698i63IOf5yVndJIDcb8dnAaZBCIkILOxQA1W5T475TXfq\nZ9ypo2bHTsb9nWasjXyaJ9hJIggTpuTj5a2TjJliAEDTHLzk8NN8If0gqlW9WGsoBqDiEPC0\noPHSgqd77JUBxAzXvhRwytLEgGFqjS/poGiMCn1dIdgohAqTtW+gGMnMP5XL5XJL768y5J/3\nhNxx3vUiwcZBCIkEEpfb7Bk7CImuW15aA7d8KCExjSYs27x27sAOVGEngtIEXwuLVQ9KqKoW\nrh6ug826qLMkuZyc1Bd3Lh0NOnLrcxnN1OfWrf+ZCDwpN/951L69hy/efv4xp0Rcrn0nM7sJ\nc2c7d5UjCToJ0cLUyU0I2bQ9Mv4Dh9nR1HHu0ik95YWbByHUJmFhh9C3nHAhjToJQGN1UJJu\n/mzUoQEf9tgJKFXurXXjx6y++LnhVSUAFNUhq48dWmYhL6AkCCGECKeZGbEQQgAAJTmpKTnN\nr/KlSDBRAADkLZZdeDvuWnhw5KVbj999zi0m0eVVtI0tBo+ePNFGU4CXw9b4GBcRW9V3nKVW\nE7Xv12cxZx7L9J/QT1ATthEqDEIICQH22Im425tGbIwHpuP64Cmdqx83w3xJ1OI+ohIGAKrK\nS8p+7N6iZAkaRVSvMD/hQhpVEc6JmtDEnbOS/Iw7r9Q5zj3hIophEEJICLDHTsR9uhcdHQ1K\nmot4j5shPkGEwgCAGIVGo7T4UX5WVcGH+3H33+eTGB17WvTSkCHyeVqVlZVAEiNIySuQMET7\ncoIQEjlY2Ik4+/2pqf5AlmnHe9wMetN3+GqbYYgp8/xCx4n+9/Oq+9lJzF7zI85sG6ok5FTf\nUvzixUeQ70uMc/4EE4ZoX04QQiIHh2IR+rbKx2usnYJKnUOubrGUbrS0MHbRALeTtL/OXl3a\nTSATFWcdctKZEPVVTFarh3EHbsqjRykFVbJOh96dGqcgiMPXc9ffdfsdAIC0/479xzUbZaFR\nvy+ssoT98VHsvY8wLCwjeqKsqITh5KblFANZpp2KnET142bQWWrygj8pEiHUxgl3thWEiIx9\nyEkS6A4hX761wpdQRzpIuRzNF0icL7utxYCk89eFjEoul8ut/Hx2SkcAMZs9WQI5fH3Hnb//\n14WqYvbX0XcCmDyOUGEQQkiYsMcOoW8pCh/OnBQ7/mJW8OBvnbNQcdFd0e6IZXhe1ISWv8XZ\n9eksm/3ddn65OVexpuXLjn5K819Ov56916rFj95AUcbb9EIAgItzdedWbHkeMFyCfzGJLCHN\nUlGSFcw5ioQKgxBCwoTn2CGeC7M0Z8Z8YxlJTIIuq6DW2dR25JRpLkbMFj9jnwhhnj54UA59\nLfs38ykRt7Q0h9D795/AhJY/C57NZoOsjo5iXUs7PT1ZiM/La/FDNyalrKMDAAADp69fXzVE\nX0dHkLfNJXIYhBASJizsEE9FSWFhYSWHzS6uBAAgS0pJlBVxqh/TGbKk1Dcvntz+9+ieHQ67\nrp2eod+y7x0ihMnKygJZJaVmz4KSVFKSgaysrJY4fkOVlVVAodTrdqJQKFBV+WNzsrQQFcvp\nXkwmQQopoYf57pWw/PCqWIRQCxD2WDAikq/xPhaKir2m7bj44kthOZfLLS/88vyi/xRTBQUL\n3/i8wvTHJ1cMVBMD8T5b34pAmEuTZYAy5nizN16tihwtDrIe/7ZMgvqOOwOwpl/mb7o8nQXg\nfFwQR/+W4y6SHfq5+UTEp5UIMwZBwvzI2X48wv3FIYTaJizsEE9FrKc66My/w2m0pDjeUxvU\n58VWcLncohsz1AFM1ie3/TAvV3UF0F36pLl1HnvrAHRd9bJFAjRw3BmAJCElx0dKggRAocs1\nMClaEHmqxS3RlSUBAJBZhsP/3h3zKr9ScAcnXJjinNQfl1Ms2HAIIVGAhR3iuT2vPWh53W1y\n2V0vLVCbf4fL5XK5V2YogLT7RREIc2OOCoDKX/8WfmuFwkvTlAFU5txomeM38OO9QYLtCqoq\nfHf1gPdoU6XqKxakNK2nrD12L71UkBmIGQYhhASOIHPCIyLIysoC7jeukq6qquKdSaaqqgrl\n5Y3vQd/2wvSfNcdQLH2/m+vexMLGSwsTA8a4HcgQM5wzu3/LHL+BkUc4P+jISIEEqkGS6mgz\ndf2x+6mpCZEb/rJVzr4RuHxML/UOJqO89195VyjY6+4JFQYhhARP2JUlIo4nS3UBtGbHFjVa\nUnhjhiaAwM4z3gAAIABJREFU/vJELpdb3UnWft5tkQhT8sDHlAYAVFULtxW7Dp+7duv27bhr\n5w7vWuFmoSoBADRTnwcEOLeMSKoK3vy7z8u5hyIFAIAkoz1oxqbTibnCGaAlVBiEEGp5WNih\nOkmbelEAmN0nbop++DGHU8mtLM75mBC1cYKRHICE2ZZXXC6Xy322ojOQhxxs6Tl5CRMmJ27t\nENUmZ0CjqA5ZG5fTgodurYo+xAatGG/Sju/qVJJMF1f/+2yRChMzU+ObNLV0uxj1GeQ6d2Pk\n49xmL89BCKGfgoUd4lPx4bCbPm92D7I473+hZGePYx+rJ+3P+nf97NlrzqWJVJji5Kv7/jd9\npE1vo066up2NetuMnP6/fVeThXfue2Ve0rVj/6zxnj9r2rSZ873X/HPs2qs8oXdDVeQ8jd4+\nZ2gnOTEAAFqHvm6+h+6mZb6M2TnLSk0cQGH8aUKF+dqyCc5MZrFYDHrtG5csKSXJe0xnMKVq\n5ughqzoEJJW3bBSEkOjAwg41UPz+8p7FE4f2MdDV0tDSNegzdNKSPVeSG1+cKnphCKIy4+ra\nEfoyjTsQZfRHrLuWIZTen+KPt0JXTTRvTwMAIEnrDJyx5fTTHP7bd1VlhTjKAHMaocJcbeko\nwp+yByEkcvCWYogn982d1zm09obGHVr+7litKwyBfDo+oc/YQ6mVIKVpPniAWRd1BToUZ398\ncefKpfgPRUDuMP7onQgXVQEmevKP4/j/XXjOrgSyfDcH95mzZk4cqCPT+G4gr9f10F/ekcs9\nQZwwx7knXFowTGXcvI79Y0beSdzem1Z/Cef2PAPzKIfY9/79yMU3Z3a22qu4PvmBt2YLhkEI\niQxhV5aIOE6OIoGE8xFiXApAhDCpt44cOXHnkzAjNJC6z1oSgKo3fv+DhgOvlbkP9o/XowLQ\nbfa3/Dg5n+POIKHc03VF8M3UZrtS2QnH/vnnAqHCtHAvGSGm7EEIiRq8pRjiYbFYIE6nS3x/\nTQEgQpg728eOveh21rl3TQfYva1O/7tsuuLicgthBfJff53DHB52PXyiasNeKDGmybTwaxIF\n3dzPrPO/O21zb0GFMvvfg9TOJu2avLyEn1yP0XN6iFQYQkzZgxASNTiPHeIxtbKSKr53+6lQ\n7zxai1BhanxJvHzp0qMMoR3/1aVLH0B3hm/jqq4Gqb2b7wxd+HDp0mvBpVIz/IFCSlAIFUZD\nQwM+nAyPK260pOhm6MkU0NTUBACAz58/g4KCgoDTIYTaKCzsEI+Uy7qtA7O3u8+Pet/4X5FI\nhyGIDx8+AN3MzLC5dYzMekvChw8fBBQJACAzcraV9dTDaY0WpB2aYmXteTJbgFkIFcbQbVov\nSvLu4RaTNp95lJpbUgVVnNzUh9GbJvYdvveDhNm0Sd0AAJ7fuJlNNjDoIsBkCKE2DIdiEc+D\nvWtvKxq2v7nLqdNR/Z7GndRVGdR6XUM954TMNhXFMARRXl4OFInvjE5LSFAEO66XG3Vg380C\nv2C1RkvUemuxJ/gciPJxnsoUxTCgvzAy9PngKaHhi4eHLwYgi5MrK6q7oCU7e4RHztcDAMj+\nLGUze7XdEFlBpUIItW1Y2CGeD9dDQ09WP8x+FX/lVXzDFQodBFdLESoMQaioqED+8+efYEj7\nb66T9vz5V1BRURFcqheJiZWsEaZaTSzSMTVlVFxITALoI4phAMgaY0MemU0I2Rt2Lu7xm4yv\nFeKyyrrd+ztMmjHZVrPmSlmFgd67BgosEUKozcPCDvEM3PLo0YrmVmA09f+yhRAqDEEYWVrK\nbQnb/8/9uRt6Nt1vV3Zv14F7IOdmaSS4VLm5ucBisZpc1q6dImRnC3D4k1BhqklqDZi5ccBM\nQR8WISSqsLBDPHKaxsbCzsBDlDBFh10ZUTUfk4riIoAzbgzG1IZrDQ9jhw5r8SziQ2ZP1w7d\ntNnZVedC2NSu0g0WFz47OMll82uujvfsweQmd9AiWCwWpL55UwrdqQ0Xlbx9mwaMgQwRDcOv\nqoSdlZVfJiGnqMig4anNCKGWg39hUGMV7JRnD27ffZcv7CAAwg9TXpRfq6gcAMqL8xsrKhNI\nFvGeK0O8DMVTT0/roW/htmLX4XPX/rtz59a1c4d3rXCz0DeZdjpV3HBx8HJTQX5h62FhQeec\n2b4zqeF5feUvd247w6H17WsiomEAAKAs+dzaSRYd5WWYyuqa6spMGfmO/Sati0nB2U0QQi1E\n2BPpIWLJve0/xpBJBgCQm365pjHziIdR117Lb1Q0u2nbC1NZxvlBZYK7TWvVl2urByg3WbmJ\nKw9Yfe2LwO8pVhrvpS0GYvImU3fGPHyTXlBckP7mYczOqSbyYiDW8e//SkU2DJfzeEM/BgAA\nSUJOVdfIxFhXlSFBAgBgWm5+SoypwBFCbQwWdqhOxYutZlIA0trWw81U+WopbkHkSClQmX1d\nkDUDocIQTVHylX0rp4+07mXUSVe3s1Ev65HTV+69/L5ISHFKEwMc2jce/SW3dwxIFGwlRaww\nL/y6iwFZ3W7VqRf5tW/XqvyXp1fbqYsB2WT9S8HGQQiJBCzsEE/xqXFyINHb72kRNyvAkr+W\n4haFOJDBaM0bEQ2Dvqsq98kxv+lO/Yw7ddTs2Mm4v9OMtZFP84RUfBMkzMtVXQG6LH1S3mhJ\n+eOlnQG6rU4SdCSEUNuHF08gnoSrV/MlnRZ5GdCh4aWD9E6dOsDttDQAHVEM01BZztvExHfZ\noNjZ1FhdGk9UBQAS03D08r2jlws7BwAQJszbt29By3OEYeO/suJGw+011+96+xZAXwjBEEJt\nGf5PQjw5OTmgqqnZ5EQaZDIZCgoKRC9M0ctTfrPHjRozeeG2mA8lAMC+6Wenp6Zraj1kiLWJ\nhkrXScEvBXPlRGtQVcLOTE1JzWSXVAk7CgHCUCgUKC5u+sYpRUXFQKEQ5u5nCKG2Aws7xMNk\nMnn3JW8g79GjD4Kd9pYQYbhv9gw1c16558iJyJDtf9v3nRaVdNhjxMqLH4Gl1bWbTju6WGFS\n+BSHpfGlLZ+F2Ah17SdRwhgaGkLmiX1ROY2WZJ3ad/ILGBk1e3c4hBD6JcIeC0bEURgxggZK\nUy6XcBuc1pZ7dZY2CRhuZ8tEK0zZ+cksAGqXcRvCIyM2TzSQFDfqbiAmZ+l7L6f6fK2vj3fa\nKwJIjTomrMsWCIFQ134SKcyXiBGyAJLaQ71Drj378KWwpPDLh2fXghcP0aIByDkfyRJoGoSQ\naMDCDtUpufV3RzGSip1fzE2/viA37cyX1/cu7l9orUoBoBiseSK4OT2IEebBIk0A7cUPa866\nT1zeCQDUF93hP/RrX0OA9vNut3wawiLUtZ+ECsPlZl1c2F2miS/UsqZel3MEGwUhJCKwsEP8\nShMDhqk1PtebojEq9LWgZ7ETfpjosRSguJ7gXU151k0KYHBwAf86VafG0YAyNloQeYiJUNd+\nEipMtdLUm/uXutmbG+ppaWjpGZrbuy87EJsm8FlgEEKiAq+KRfwkus2IetYvat/ewxdvP/+Y\nUyIu176Tmd2EubOdu8qRRC5MWVk5yMrVHYvBYABIS9e7lRdJRkYKystE+PoJQl37SagwuW/u\nvM6htTfsP21d/2kCOiZCSORhYYcaIMl1dVr8j9PiBs0VOU/OPaWPsNYlQhhEIIS69pNQYW4s\nN3eOHnnk6wlXwR0TISTy8KpY1DxuUfL1g8vH9VZvb+y0+4ngjvsxLiLiZnLT81R8fRYTERH3\nUXBhUDMIde0nocKwWCwQp9ObnLIHIYRairDHghFRlWU+OL5p+kBdmeqRSJKM7oCtCYI7/HFn\ngOHhnCaXvVxjBOB8XCAZSBJScrWkJUgAFLpcPVISJIGEIS5CXftJpDCFR12kQN/7scDPTkUI\niTIcikUNcAveXj18cP/+kKiHmeUAIKZoMn76rKlTxlhpSgk7W43KykogiQmmt5lbVpRf7wS6\n8uL8fIEcudVQ/H97dx5XU/rHAfx7u3XTpk20yS0lhKIoFbKEkNJil1LGNobBDIOZYSxhkBnZ\nKkvWpIgxlIgQMSVZIqGkFDcp7cvt/v6IoUXMzK9zD/fz/ut2nsP9vNRM3/uc5/s8EwJDbzxx\n33hqjeepNXVGWlp8FxYwtpWkhlFwW73Bvvccz7mW4WudDeQZfGcAkGAo7OCtytzrx3YHBASF\nnH9cIiLitTF3MSk6GvN85Mr9K4aKO9z7SlNSMknNRq3Z38jlUFmZ8JPu5Er247ZWQzbEpzgF\nb911PDYpLaewSkZZy6iHnfOUmR59dBj/l2FPmITtq65qdNOJ9R/VMcS4p1lHPW0V2TpdPz2/\n3jPLgtFIAPDl44hEInFnAPGqKUw9sz8wMDD4RHJeNRFPs8eICZ6eXhMcTNQi3DjuZ71PFwQx\nVthd2zTWL56IKCvucJzIyt22Xd2JOWF5QWbSxeuZNHJv7vFJLZmKBR/2tvfTrC0L5qRYFSbM\njeMe3tQNrkdEYW5MpQEACYEZOzjm09EtjIjXpofrPE9Pr/EOXdS5Ygvz9PLhw+9+F8YfORzf\n8B5ZLauv/PzGo6pjB1b1frIqjP36pKSlTd2gos9UFACQHCjsQCQiIo66mYOLi6vzQHFWdUTk\n4J+WtoaIKHK20ezq9Xe3OdV5esbh8hTVtdq0xOHp7MGq3k9WhVHmm5mJOwMASBxsdwKWU1dO\n6ccvv75n6QQbvpbx4Gm+h+Kzy8UURkHTsJb9NF/fGUONDetqr6+Hqo5lLOzsFEqvX731aasR\nmxmrwgAAiAEKO2g7ZMnOC49yHkRuW+BqxkuPDlg8vreeZqeh09cevpkvtlTGzosWuZiIdfYQ\nPomC2+oN9nl+nnMjHje+MbDEhqHnobPs+vsczGowkHXA267/N+F5YsgEAF86NE9AHZXPEyN2\nBwQEHYp5VFT7kyFrPjN469JRvbTE8nirOv/B1ct/pWbnl1QI6/6kGo2YO9xQHJGgroQtnv5X\nMi+FnX8saiX23k9WhcnfYd96+quVjxMWNVhL93ClmdFyzcAXkT6qDIUBAEmBwg4aIyp+FHMo\nMCBwT8RfzyuJSFq96zCPqfO/n91Xk7kQry77ekz85eSTxh8Lo6OQJVjV+8mqMJe/1uwT4hyd\nt31Qw7FIH1WH0x5Xsn/rzVAYAJAUaJ6AxnAU2w+cumbg1BWC5BPBOwICD569fcLvGxnr2X0Z\nq6XyQqY6Lj5JPT1XOFfsW3JUe77/KNVHt2IO7Y/Jaev+85KRfXoxlQSaxKreT1aFyc/PJ3V1\n9UbHWrfWoLw8PIsFgP87zNjBpyjNuHA4KCBn4MHF/Rl6x9zf+mjPTfM6k77TvtDfVmtRx9PF\nQUOJqPzRAe/+k6+OPJPsP0CJoSwA/0bcbC3bnX0OvwodLVt/qDx0tNqYWK+Lz7f0EUcyAPiC\noXkCPoU8385rJXNVHRHdSk4WqYxwt5cj4nA4VFNTU3u9RfsJW1c4PNuxar+AuTDwuci8tH9/\nbHpNo2Ov75zav/9SJnNhetjayped8Pv9flW9gap7v288UdbCxsacuTAAIClQ2MEHVb58mHgh\nKurCjczixn9TNuubV1aSRuvWREQ8Ho/KC9+d2KpsZqZfnZiYzHgmYL3rv02a5BdX2ejYs4jF\nkyb9dp25MHKj5s1qXxW/yKb31M2nkx7mFpcV5z5MOr15am/bH65VGcxa4MaC4zEA4EuDNXZA\nRFRy76iff1hynmxbS/dvZg7jtyiIXTlu8qrIN40Lih0n/X40yKsTg42xmpqab9cgqejqKoqu\n3r5D43oQEVFlRkYOc0GgMTP5/FOfeu+wbRlbHZozzCcSCoXEkWLysyyv98qILfeGfn0y6Jth\nQe8PcHUctxxfbc2OfZQB4MuCwg5IlLZ1mNWsi6+JiCh0z+GkY+cc9jr/GFnYQl3fRIsrePz4\nxf193iM0jFM2WDdYLNRcOpqa8l6lpOTSYE2O9QA72b075q0euGuGpUrOmR+XhhZyLbuZMBUF\nGiovLi5+/2thaUFBmZCIiCunwKsseftaRUWeW14tjoQNlKakZJKajRqjb8rrMv3EbesjW7eG\nRF27l11QyVPR7WQ1ZNzMmW5dVTgf/+MAAP8Ymieg6tQUreG7izuPX/6Ds27uH2t/OiTVsdPt\nx2rLoo8u7anGISpK3jzO/ps/S90PvwgdzdjDo7yAwW2mF23MvDpHlyoTlvXss/zW3/uecA3m\nnL29yQ4PstihOH6Fg+Om0uFLViyY0LdjG0Xp6uLn9y8eWL901Z8Kc0+e/tFSsbkTXNs01i+e\niCgr7nCcyMrdtl3diTlheUFm0sXrmTRyb+7xSThlGAC+YCjsIPE7fYv13O9vpK3tziGiO0s7\ndV11X29BfPqvln//dkxbYdrhp5dzrmZtshJTyvzEPev8Qq9klKkaWDjO/sG7pxomPNhBGPdt\ne9sTIy7d9retV2mXXv66a5+TIy8/8rNp5iNEPrp9HRHJallN9juwdYwBjjMBgC8ZHsVCdnY2\nybj2MntTKHWxslSg+51MTN6f8zDs0qUFHXnxQiwBiYhIzdxzzX5P8b0/fMhfR4484Y+bVL+q\nIyJ520ku/C0hYQl+NpbNm8HBPy1tDRFR5Gyj2dXr725zqrN8jcPlKapr4ZRhAJAEKOygsrKK\nWior/z0BpqKiQqSoWOfxGUdJSYGqKhvvNgSJJhAI6EMT/yKRiASC5t+YRkHTsPZ4Oftpvr41\nQ40NDcU1LXd1nfPaK6Tq6Lvbu1Pt6yZYL4z4HidPAMD/Fwo7YK+agjthO3ZG3Xz0JEtQXFWv\ndBjgG7+awX314EP4fD4dDA+OXW7VT6HuSEnsnrAnpD+JwcMejJ0XLap3qfxp/OmYWy/lOw0e\n0UdPrrkDZF8/fvw4teEv+Pt1E6QnNnccAJA8KOyApcoSfAfZL7lS8KE1oLovGY0DH9LVa7r1\nhnnbnWyKFi+bN65vJx012Yr87HsXD21ctvrAE1kbv8lM9i/fWjfAZafu6vi9o1WJiIovLbEd\ntjq5mIhIvuu8U5c39Gve1onhAU+fbiKuUuu/XzdBvvHjxgAA/gM0T0CYG8f9KE+hpdybKl9Y\n9rq4UlpeWf79FUnVZa9LKl0YPEA9a5Mt/9u4VoOW/r7Ss29HnVYK9T+DSHGlpdA/wQo1WeHT\nh3oE3i0lIiKuNFdYLSQiIgWTr/ZGbXPRYW7vuKz1Vm0Xyvnnnp+lQUT0ZL1V+++S2jnNn9ZT\ncPTXoOuGvvcTFnVgLA0AAPMwYwdERKLKksI6C+iqSgsLxRWGiIhuJiQIZUasPbpiNE6EZTsp\nXdeARItxwduDj19MSssprJZW1jLq3tfJc8ZkOz3Gdj4kIqLHjx9T6zFdNGq/yjlx7JpQZ9bO\nsNV20uSp+khnVkjow0VLDRmNBADAKBR24HKorHY72Y/iMrhTfsuWLUlVTw9V3WdCtl3/r3z7\nfyXuGAUFBaSm9mYT4oq4uERS8RjZV5qIqHXPnnoUmJlJ1MyFXW7iyYRPOxpFy2KEuWbzhgEA\niYPCDqRkWrRg3z4QPYcMUd129cojUf/2eOAKn0pNTY1ePH9O1JWIrl6IrZCytLZ68yRYKBRS\nRUVFs2e47Ov40U31arkyuLYBACQFCjv4NNUvk0/eknfub8TQ+8mNXLPd3dJ7/IJuISsd9Zu9\nmRG+DMZdukhvOR545Kf+btLh/odzOb0XDn7TLVGdnp5FmpoMzZBJq5sOHmKm0fQnpp58ZsIA\ngCRBYQdNE5WkXzgUFBi4++j1nBFHRIwVdsTRGX3wfP7QXiM77tbvbGKorcyrO3Nn+8PJRTZM\nhYEmCXNit67YsD/6emr2q5JKYb1+LNfQ6sMuDCXRmDBn/NKRe0fr/SHHLSurVHXdPF67dkR0\n7Uq8kGdp2rHZM2gZd1aVSnmZHH2WO9LDx8dn/GBjZebaRwBA0qGwgw+oepF4PDgwIPDg2bQi\nERFHyWiQtQGT7/8gyMVu1rkCIkq/eTn9Zv3xFp4MhoEmvDw5tZfT7qwaDk9Zs61RO0Xpes/O\n9Zg8m1XJcUvMbrUfAy88JW3L8T/7jm1de73q4rGzFeqDBts1/+Svzaq7z2bEhe0KCtp1ZP3M\n8PUL9GzdvHx8prj30cPpxgDQ7LDdCdQjKnp47mBQQMCeiBvPq4hISsN83LSZPt5j7PgKH/3D\n/z95Ox30fCJle01bscTD1li74XYn8uq6anhCywLpaywMfrjZYcreoxvHmShjQeR7al6nRR8M\nCgoKPpH4vFKqpbH9OG9vn8lOFq0Z7EICAEmDwg7eqsy9fmx3QEBQyPnHJSIiXhvzESZFR2Oe\ne58uCBrKeJooL6Wh+6y2P4+ehk1c2e3kxBaOYY4hr4+MYXu5wvQ60XdvLLj5R3Bg4M6DUfcL\namQ0eiw7mbi4F9MhAEBCYOkH1BSmRm5Z4Gqm09Zy7OKdMVlK3V3m/37iTk5WQviMrmJLJSMj\nQ62MjVHVsZ6CggIpt2bzJJSoJP180JLxlno6ZqO2JIshgLSG2agFW45FH13joCtdJUhOeSaG\nEAAgIbDGDo75dHQLI+K16eE6z9PTa7xDF3VxnaD+np52dvKBiYlZZKcr7ijQpF6DBikFXLuW\nTv0ZPBP204h7nWit6rxbJ/ftDNq5P/JuvlBGo/uoye6mjIcAAImBGTsQiYiIo27m4OLi6jyQ\nFVUdESmNWbdp8MMVk365/OLTdk8GMVFwW+fvmLXGazl7vlOioodndywabd5W18L9+x3RaSWt\nzCcs3Xn+cc6D6Hk9GEyRFh2waEyvtjqmo+b5X6oyn7r2cEJW1o2jvzqxrgQGgC8H1tjB06hV\ny3x3Ho5NLyGSUu4wcIynl5fHKCudFrXHyJ4Vzxq7hC2e/lcyL4adT5dtZ2HZ3ajBdic9v94z\ny4LxWNBAwhZP/6tPLx+JeSTbzqKXmZGOivi+U+xYJ1qWdSV8d1DQrtDYjBKS07Vx9fTx8R7d\nj4+eWABggghAJBLVvH4QuW2Ba483O6pKKXccMm1NyJL+RMrep8UR6IjrR35yXY+IIxY0wIbv\nlLDg/mn/+S6mrWrXlvA0e7jM//3EnZdVtfGY/Rk+OlqKiKQ1zJznbT5571U1g28NACDCjB3U\nUfk8MWJ3QEDQoZhHRbU/GbLmM4O3Lh3VS4vZ1fGFGTfTC5q6QUXfjK/MVBr4MDZ8p8LdOW/W\niTpOqLdOlPlZ5zA3jnu4dEstHdWP/SczbFvGVgdGMgGA5EDzBNTBa2M+etGO0Qs3PIo5FBgQ\nuCfir+eJW8daBqh3HeYxdf73s/sydWa5Mt/MjKG3gv+EDd8p9q0TrX6d8+T1x256UcJEFACQ\nLJixg6ZUCZJPBO8ICDx49kFhDc4sh6ZUFzy5//BZiWpny/ZMT6Wyap1oTVV55ae1kXB5LWTQ\nvwYA/18o7OBTlGZcOBwUkDPw4OL+zL5xdf6Dq5f/Ss3OL6modwSp0Yi5ww2ZDQMf8ir+txnT\nlofdeiUk5WnRBdsHERG9CPEevPLOiC1XVvZjZAZNVJR25kBAYGDwiRuCKiIp5Y72Yz29WkWN\nXXVDPA1AAABigMIOWOvVZV+Pib+cfFLe6CimD9lCeG+jbc/58Zz2/QdqpB6/5/i2sKPiI66a\no696ns/2t2PypDHWrBMFABADPAcAIiq+Hrxqpe/h2xVvvr7yUy/DunotOFvKbKa8kKmOi08W\ndvVcsWpcB5K1mx/428pF3gPayRLP0H3V7n1zcCYTO5SdWPlLfJXlyiu3YoIm1zmtS3H4yP7c\nnMuXHzEbqHad6Nm0Z2lnAxaO7tmGRxWJW8da6ml3c5q3+WIus2EAAJgm3qZcYIVUXzMp0ptx\nrvTthUYOaJUyW5PKZKacTbYcajPlTKlIlLPZhhTeblhR9nD/+LZc/VnnXjOZBj7s0qw2JDfm\nSIVIJBJs60fK06LfjcUv4JP6tPPiiiYSiUSiyhc3w36dMbiDshQRdskBgC8eZuyAkoJ33xT1\n+HrBALk6l0cE5rwVv7RLzc1dwUkMhrqVnCxSGeFuL0fE4XCopqam9nqL9hO2rnB4tmPVfgGD\naeDDXr58Sdp8fqNPOblcLhUVFTEdqQ4ZDVPXBVujUp89Or9rybgeOH0YAL5sKOwgOybmAXV2\ndKx/iKasiuZblh6ju9GDCxdymEtVWVlJGq1bExHxeDwqLyysfDukbGamX52YKI7T3KEhVVVV\nEggaLbNfJSVlkJaWFtORGiXPt/NayXj3DwAAw1DYQWpqKnFNTIybukffwIBDqampTGUi0tTU\npLy8PCIiFV1dRdHt23feDlVmZDBYYcJHmNvYtHj9Z/jZivoDr2KWro0WqtjZ4ch7AADGoLCD\noqIiUlRSer9v0XTGvmPHFlq/uyCtpqZEhYWFzKXqaGrKe5WSkktEHOsBdrJpO+atPvf4VXF+\nytFvl4YWcrt1M2EuDDRBwW3BLAPBLo9Rq06nvKwmqikTpP0VFTh/QJehWx9Jd50/b5iMuCMC\nAEgObHcCZ31U7PfYh1QcGfPh3caEIW68cTHe5/IDBjAVKy9gcJvpRRszr87RpcqEZT37LL/1\n974nXIM5Z29vssOh6ixReWe7u8PsE1nVdS/LtHMPij7kYST+cyAAACQGjhQDPp9PwsSEmzTG\n/IP3JCUk1lC7du0YjNXqqzPCr9685lksO3+Zv84v9EpGmaqBhePsH7x7oqpjD16X6RF3+kTs\n2H4w8urdzJfl0so6Ha0cJs6e5WqizOQOdgAAgBk7oLhv29puqvaJfBg4RKHRG0oifdo77OR9\nG5e50brRGwAAAIANsMYOyGb6TFOp3J1TxgemNLIJccndwHHeO59Lmc2azmRVl3lp//7Y9JpG\nx17fObV//6VMBtMAAAB8FjBjB0RUkbDM2nb5jYoWuv3GTxltb9mprZqcqOxl1r3r0aG7DsZm\nlcuaL4uL+9lclrlIYW4c9+p9ZRETWzQcu7/SrNOPhjhSDAAAoB6ssQMikrX4+UwUZ8yYledi\nd/3TagIUAAAKL0lEQVQSu6vuoLTmoGUhIT8xWdV9hFAoJI4UZpvFaCaff+pT7x22LWOrQ3OG\nAQCAv6GwAyIi4qj3+/ns44ln9u4Jj4q7mZ7zqpQjr6qpb2YzxNXLY7ABqzoVSlNSMknNRk3c\nOSRZeXFx8ftfC0sLCsqERERcOQVeZcnb1yoq8tzy6sb+BgAAaA54FAuscm3TWL94IqKsuMNx\nIit323Z1J+aE5QWZSRevZ9LIvbnHJ7UUS0aopzh+hYPjptLhS1YsmNC3YxtF6eri5/cvHli/\ndNWfCnNPnv7RUlHcCQEAJAYKO2CVMDeOe/hH7pHVsprsd2DrGAPsj8YGwrhv29ueGHHptr9t\nvYnd0stfd+1zcuTlR342+FYBADADhR2wSknuw5xiIqLI2Uazq9ff3eZU53B5DpenqK7VpiXO\nMmCP+Lm6vY+Pi0//1bLh2LXv9K1CnOOf+jUyBgAAzQBr7IBVFDQNDYmIyH6ar2/NUGNDQ8z1\nsJxAIKAPfT4UiUQkEAgYTgQAIMHQWQjsZOy8aJGLCao69uPz+fQkPDi2pMFISeyesCekr68v\nhlQAABIKhR0A/BddvaZby2Zsd7KZuC7ixtP8shqqKct/eiNi3UQbpx1PZG2mTTYRd0QAAMmB\nNXbATpGzDb8+3dQNDv4PNw9lKg00pSYrfPpQj8C7teeWcKW5wmohEREpmHy1N2qbiw4+PwIA\nMAVr7ICdKl/n5eXVuSKqLHldVk1E3BYtFWU5ryvFEwwakNJ1DUi0GBe8Pfj4xaS0nMJqaWUt\no+59nTxnTLbTY8++1gAAkgAzdvD5qHr9NOn4+rnfHWu1PCp8Wie0xgIAANSFwg4+N6/+nGTi\nlDwtMflnU464s0BdNeUFAkFhJU9ZQ0OlBR7AAgAwD//vhc+N6jD3QS1uBx9IEncQeKcy/eQq\nD1sDNSVVTT2+nqaqkppBH4/Vp55UiTsYAICEQWEHnx2OrKwMZWdnizsHvFGevHZQD8el++Iy\nyhS0jUzNzYy0FcsyLu9bMry7/frbFeKOBwAgSVDYwWdGlBsW9EcB6ejoiDsJ1Lq3wWvxpSI9\nh5+P3hW8yn5wMyHpQXa+IOXYMge9wthFXn73xR0QAECCYI0dsFNK6LLQlHrXqksET+/ERETd\nf801+yUx8cdu+FzCAveXdem0XPRDcvLqbvWa7KuTF3cz8+Uuu3/7Z2PxZAMAkDjY7gTYKSV0\n+fLwRkfk2g5c4L97Cao6lnj48CHpf+Ncv6ojImlTp+F8X/+HD4lQ2AEAMAOFHbCT7Q9//OFZ\n9xJHiienqt2xa2dtRRR17CEjI0OlpaWNjpWUlJKMDPalAQBgDAo7YCdN8xEjxJ0BPkW3bt1o\nT9iOiOV2zup1RwRHd4S/IFPTbuIJBgAgiTDzAQD/hdbEmc4tn4eMtxz+Q/D5u08EJRUlgid3\nz+9Z6GA5IfSFsuusCZrijggAIDnQPAEA/1Fe1PzB7huTiupfb2nxXXjUukFq4sgEACCZUNgB\ne1xd57z2yqfebL0w4vvezZkG/onKrIvBW3cdj01KyymsklHWMuph5zxlpkcfHZ64kwEASBQU\ndsAeYW4c98Y7YRvhekQU5tacaQAAAD47KOyAPcrys1423l3ZCHl1XTW55kwDAADw2UFhBwAA\nAPCFwHYnAPBfnJ7Jn3HqA2McKZ58y1a6nSwGunhPdTNV5TCaDABAAmHGDtim+Hrwb2eeGTrN\nG9NVlojoyk+9PA7mv3+HmvP2C+sHyYsnHtTzx5RWXieEZQUFpUIiIq6cAq+ypKz2tbxKS07x\nq5JqIuJqj/CPOTbdGJ8lAQCaE/axA5Z54D9tytLApxqGsm8ulL54/Kiuv/y+2/xArCHhHcdd\n6X9800VBrdfU3yJTXhSXlxaXlhe/uBu5ydtCVb7Lt9GC4pyb4UvttXJPzvb6/ZG40wIAfOEw\nYwfskrTEuIev4rqHid8ZvLlydnor+x29A3MC35xE8WSLvdXKysU3Uld1F1tKeEd4aY5B31Mu\n8bf9LFvUHSm7OqerdcSIi4839eGWxs7oZLddw1eUsEg8MQEAJANm7IBVsmNiHlBnR0eDetdl\nVTTfsvQY3Y0eXLiQI5aAUN9f4eGZ+qPG1a/qiEiu9wQX/czwowlEJN/PbVgrSk1lPh8AgERB\nYQeskpqaSlwTE+Om7tE3MOBQKmoElhAIBPShif+amhoSCARERKStrU1VVUwmAwCQQCjsgFWK\niopIUUnp/e5J0xn7jh1baP3ugrSamhIVFhYyHg4a065dO8oI33ep4Q6EJbHB4U+Iz+cTEdGz\nZ8+oVSuGwwEASBoUdsAqCgoKVFxYKHzvkoapg7NzT+13F4SFhcWkpKTEeDhoTLfJU3vJpG9x\nsvX49UTS0/zyGqopy3964/i6STZO2zN4VlM9uhAR3b0Qm8ft2lXcaQEAvnDYewBYhc/nkzAx\n4SaNMf/gPUkJiTXUrl07BmNBE4znhQbfHeIdvO97p33fE3GlucLq2spcrtOUfaFzOxAR5T1T\nGDBrmcNQsSYFAPjyoSsW2CXu27a2m6p9Ih8GDlFo9IaSSJ/2Djt538ZlbrRu9AYQh7L0s3u2\n7z156WZa7utq6ZaaRt37jvCY7jWQ37CnAgAAmg8KO2CZVF+zzotvaY7cEX1oauf6mxCX3A0c\nN/irP3LN1txLWthBLPkAAADYC4UdsE1FwjJr2+U3Klro9hs/ZbS9Zae2anKispdZ965Hh+46\nGJtVLmu+LC7uZ3PZj/9VAAAAkgWFHbCP6GXsL2PGrDz3vLrBkLTmoKUhIT/1U8epowAAAA2g\nsAOWKn10Zu+e8Ki4m+k5r0o58qqa+mY2Q1y9PAYb4JBY8Vvn7HyFVB19d3t3urrOee2Vpu61\nXhjxfW+mggEASDgUdgDwj7lxOOHUZs6l3E22YW4c9/Cm7nU9IgpzYyoYAICEQ2EHAP9YflZW\nKXGVWmsp88rys1423Jz4PfLqumpyTAUDAJBwKOwAAAAAvhA4eQIAAADgC4HCDgAAAOALgSPF\nAOAfW+fs3GQn7PvQFQsAwBwUdgDwj10/fvz4p94rPbE5kwAAwPvQPAEA/1h+VlaTnbDvQ1cs\nAABzUNgBAAAAfCHQPAEAAADwhcAaOwD4b2oKUmPPRMclPcp5WSJSUNdu391m8OB+HVTwsREA\ngHEo7ADgX6t5HrNm+sw1EalF9QaUjJ1/2LZ9Uf82HLHkAgCQVFhjBwD/UvaRib3HHXgqJAW+\n9ZBBVp31WslTaV5mSvzZqCsZJcRtOyEkfr+btrhjAgBIEBR2APCvZAUM6DDtfE2HCZsP+nub\n13nwWvMqcefs8bMPPOAOCHhwbqqO2DICAEgaFHYA8G/EL9DvvaHQae+dY5O0G3veKsoOdu7i\neUJlQXz6r5aMpwMAkFBY3gwA/0JqVFQGGU3/pfGqjog4OpN/mW5EGVFRD5hNBgAgyVDYAcC/\nkJGRQfJWVt2ausfUylKOMjIyGIoEAAD0P7guSEAYI+C0AAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.height = 10)\n",
    "\n",
    "f1 <- colorRamp2(seq(min(plotMtx_pctexp), max(plotMtx_pctexp), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "ht <- Heatmap(as.matrix(plotMtx_pctexp), name=\"log2FoldChange\", column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", p),\n",
    "              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx_pctexp),\n",
    "              cluster_rows = TRUE, show_row_dend = TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx_pctexp)*unit(10, \"mm\"),\n",
    "                 cell_fun = function(j, i, x, y, width, height, fill){\n",
    "                     if(signif_df[i,j] == \"Yes\"){\n",
    "                         grid.text(\"*\", x, y)\n",
    "                     }\n",
    "                 })\n",
    "\n",
    "draw(ht)\n",
    "\n",
    "# TODO: OK OK ADDING \"*\" WORKS; NOW I JUST NEED TO SUBSET signif_df TO MATCH plotMtx EXACTLY WITH SIGNIF COL\n",
    "# basically need to make a matrix with Yes/No with exactly dims as the plotted data to i can say \"psignif_dfdata[i,j] == Yes\"\n",
    "# ok this works but i need to make sure the right genes are being plotted - aka i can't find Ets2 which should be there for microglia\n",
    "# also check that the * are placed correctly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "056ff51e-8285-46df-894a-39fd19a49442",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e23f7767-9fa0-4b91-ba50-19196a9a604f",
   "metadata": {},
   "source": [
    "### done testing now put it all together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4001a323-f6d6-4150-833a-c4fa0088c35e",
   "metadata": {},
   "outputs": [],
   "source": [
    "### putting testing heatmaps in here so it doesn't overwrite the other stuff\n",
    "# this directory is a remake of the log2fc tri16 hmaps - with the NA's introduced from deseq2\n",
    "NA_ODIR <- \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/includeNA/\"\n",
    "dir.create(NA_ODIR, showWarnings = FALSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "db786aeb-e3f0-4fee-9d93-1f9bb97e5aaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "sobj$broad_celltypes <- factor(sobj$broad_celltypes, levels = c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN',\"GABAergic\",\"Glutamatergic\",\"Doublet\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "9202a2e8-e3b9-4b22-9274-38f860f74ffd",
   "metadata": {},
   "outputs": [],
   "source": [
    "plotHmaps <- function(hmap.df, odir, signif.df, title, pctExpThres){\n",
    "    # log2fc scale\n",
    "    write.csv(hmap.df, paste0(odir, \"log2fc_hmap_\",pctExpThres,\"pctThres.csv\"))\n",
    "    #f1 <- colorRamp2(seq(min(hmap.df), max(hmap.df), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "    f1 <- colorRamp2(c(min(hmap.df), 0, max(hmap.df)), c(\"blue\", \"white\", \"red\"))\n",
    "    #f1 <- colorRamp2(c(-3, 0, 4), c(\"blue\", \"white\", \"red\"))\n",
    "    ht_log2 <- Heatmap(as.matrix(hmap.df), name=\"log2FoldChange\", column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", title, \"(<=\",pctExpThres,\"%)\"),\n",
    "                  show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(hmap.df),\n",
    "                  cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "                  row_names_gp = gpar(fontsize = 10), width = ncol(hmap.df)*unit(10, \"mm\"),\n",
    "                        cell_fun = function(j, i, x, y, w, h, f){\n",
    "                          if(signif.df[i,j] == \"Yes\"){\n",
    "                              gb = textGrob(\"*\")\n",
    "                              gb_w = convertWidth(grobWidth(gb), \"mm\")\n",
    "                              gb_h = convertHeight(grobHeight(gb), \"mm\")\n",
    "                              grid.text(\"*\", x, y - gb_h*0.5 + gb_w*0.4)\n",
    "                          }else if(signif.df[i,j] == \"nd\"){\n",
    "                              gb = textGrob(\"nd\")\n",
    "                              gb_w = convertWidth(grobWidth(gb), \"mm\")\n",
    "                              gb_h = convertHeight(grobHeight(gb), \"mm\")\n",
    "                              grid.text(\"nd\", x, y - gb_h*0.2 + gb_w*0.2, gp=gpar(fontsize=5))\n",
    "                          }else if(signif.df[i,j] == \"--\"){\n",
    "                              gb = textGrob(\"--\")\n",
    "                              gb_w = convertWidth(grobWidth(gb), \"mm\")\n",
    "                              gb_h = convertHeight(grobHeight(gb), \"mm\")\n",
    "                              grid.text(\"--\", x, y - gb_h*0.2 + gb_w*0.2, gp=gpar(fontsize=5))\n",
    "                          }})\n",
    "    pdf(paste0(odir, \"log2fc_hmap_\",pctExpThres,\"pctThres.pdf\"), width = 8, height = 11)\n",
    "    draw(ht_log2)\n",
    "    dev.off()\n",
    "\n",
    "    # make a version without nd\n",
    "    #ht_log2 <- Heatmap(as.matrix(hmap.df), name=\"log2FoldChange\", column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", title, \"(<=\",pctExpThres,\"%)\"),\n",
    "    #              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(hmap.df),\n",
    "    #              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "    #              row_names_gp = gpar(fontsize = 10), width = ncol(hmap.df)*unit(10, \"mm\"),\n",
    "    #                    cell_fun = function(j, i, x, y, w, h, f){\n",
    "    #                      if(signif.df[i,j] == \"Yes\"){\n",
    "    #                          gb = textGrob(\"*\")\n",
    "    #                          gb_w = convertWidth(grobWidth(gb), \"mm\")\n",
    "    #                          gb_h = convertHeight(grobHeight(gb), \"mm\")\n",
    "    #                          grid.text(\"*\", x, y - gb_h*0.5 + gb_w*0.4)\n",
    "    #                      }})\n",
    "    #pdf(paste0(odir, \"log2fc_hmap_\",pctExpThres,\"pctThres_NOnd.pdf\"), width = 8, height = 11)\n",
    "    #draw(ht_log2)\n",
    "    #dev.off()\n",
    "\n",
    "    # zscore log2fc\n",
    "    #plotMtx_zsc <- t(scale(t(hmap.df)))\n",
    "    #write.csv(plotMtx_zsc, paste0(odir, \"zsc_log2fc_hmap.csv\"))\n",
    "    #f1 <- colorRamp2(seq(min(plotMtx_zsc), max(plotMtx_zsc), length = 3), c(\"blue\", \"white\", \"red\"))\n",
    "    #f1 <- colorRamp2(c(min(plotMtx_zsc), 0, max(plotMtx_zsc)), c(\"blue\", \"white\", \"red\"))\n",
    "    #f1 <- colorRamp2(c(-5, 0, 4), c(\"blue\", \"white\", \"red\"))\n",
    "    #ht_zsc <- Heatmap(as.matrix(plotMtx_zsc), name=\"Z-score log2FoldChange\", column_title = paste0(\"DESeq2 Tri16 Genelist:\\n\", title),\n",
    "    #              show_row_names = TRUE, row_names_side = \"right\", col = f1, column_order = colnames(plotMtx_zsc),\n",
    "    #              cluster_rows = TRUE, show_row_dend =TRUE, cluster_columns = FALSE, show_column_dend = FALSE,\n",
    "    #              row_names_gp = gpar(fontsize = 10), width = ncol(plotMtx_zsc)*unit(10, \"mm\"),heatmap_legend_param = list(at = c(min(hmap.df), 0, max(hmap.df))),\n",
    "    #                    cell_fun = function(j, i, x, y, w, h, f){\n",
    "    #                      if(signif.df[i,j] == \"Yes\"){\n",
    "    #                          gb = textGrob(\"*\")\n",
    "    #                          gb_w = convertWidth(grobWidth(gb), \"mm\")\n",
    "    #                          gb_h = convertHeight(grobHeight(gb), \"mm\")\n",
    "    #                          grid.text(\"*\", x, y - gb_h*0.5 + gb_w*0.4)\n",
    "    #                      }else if(signif.df[i,j] == \"nd\"){\n",
    "    #                          gb = textGrob(\"nd\")\n",
    "    #                          gb_w = convertWidth(grobWidth(gb), \"mm\")\n",
    "    #                          gb_h = convertHeight(grobHeight(gb), \"mm\")\n",
    "    #                          grid.text(\"nd\", x, y - gb_h*0.2 + gb_w*0.2, gp=gpar(fontsize=5))\n",
    "    #                      }})\n",
    "    #pdf(paste0(odir, \"zsc_log2fc_hmap.pdf\"), width = 8, height = 9)\n",
    "    #draw(ht_zsc)\n",
    "    #dev.off()\n",
    "\n",
    "    hmap.list <- list(ht_log2)\n",
    "    return(hmap.list)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "f327b3d2-743f-40e3-9e15-9c6586a2d7b7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"STARTING: Dp16_yng-2N_yng\"\n",
      "[1] \"GABAergic\"\n",
      "[1] \"detected\"\n",
      "[1] 76\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Fam3b\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 38\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Mx2\"            \"Tmprss2\"       \n",
      "[37] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Glutamatergic\"\n",
      "[1] \"detected\"\n",
      "[1] 68\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig1\"         \"Ifnar2\"       \n",
      "[33] \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"        \"Tmem50b\"      \n",
      "[37] \"Dnajc28\"       \"Gart\"          \"Son\"           \"Donson\"       \n",
      "[41] \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"         \"Mrps6\"        \n",
      "[45] \"Slc5a3\"        \"Rcan1\"         \"Clic6\"         \"Runx1\"        \n",
      "[49] \"Setd4\"         \"Cbr1\"          \"Cbr3\"          \"Morc3\"        \n",
      "[53] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[57] \"Kcnj6\"         \"Ets2\"          \"Psmg1\"         \"Brwd1\"        \n",
      "[61] \"Hmgn1\"         \"Wrb\"           \"Lca5l\"         \"B3galt5\"      \n",
      "[65] \"Dscam\"         \"Bace2\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 46\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"Olig2\"          \"Kcne2\"          \"4930563D23Rik\" \n",
      "[29] \"Kcne1\"          \"mmu-miR-802\"    \"Dopey2\"         \"Chaf1b\"        \n",
      "[33] \"Cldn14\"         \"Sim2\"           \"Ripply3\"        \"Dscr3\"         \n",
      "[37] \"Kcnj15\"         \"Erg\"            \"Sh3bgr\"         \"Igsf5\"         \n",
      "[41] \"Itgb2l\"         \"Fam3b\"          \"Mx2\"            \"Tmprss2\"       \n",
      "[45] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"BFCN\"\n",
      "[1] \"detected\"\n",
      "[1] 49\n",
      " [1] \"Rbm11\"   \"Hspa13\"  \"Nrip1\"   \"Usp25\"   \"Cxadr\"   \"Btg3\"    \"Ncam2\"  \n",
      " [8] \"Atp5j\"   \"Gabpa\"   \"App\"     \"Cyyr1\"   \"Usp16\"   \"Cct8\"    \"Bach1\"  \n",
      "[15] \"Grik1\"   \"Tiam1\"   \"Sod1\"    \"Hunk\"    \"Urb1\"    \"Synj1\"   \"Ifnar2\" \n",
      "[22] \"Ifnar1\"  \"Ifngr2\"  \"Tmem50b\" \"Gart\"    \"Son\"     \"Donson\"  \"Cryzl1\" \n",
      "[29] \"Itsn1\"   \"Atp5o\"   \"Mrps6\"   \"Slc5a3\"  \"Rcan1\"   \"Setd4\"   \"Cbr1\"   \n",
      "[36] \"Morc3\"   \"Hlcs\"    \"Pigp\"    \"Ttc3\"    \"Dyrk1a\"  \"Kcnj6\"   \"Ets2\"   \n",
      "[43] \"Brwd1\"   \"Hmgn1\"   \"Wrb\"     \"Lca5l\"   \"B3galt5\" \"Dscam\"   \"Prdm15\" \n",
      "[1] \"not detected\"\n",
      "[1] 65\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"D16Ertd472e\"    \"Chodl\"          \"Prss7\"         \n",
      " [9] \"mmu-miR-155\"    \"Mrpl39\"         \"Jam2\"           \"Adamts1\"       \n",
      "[13] \"Adamts5\"        \"N6amt1\"         \"Zfp294\"         \"Rwdd2b\"        \n",
      "[17] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[21] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[25] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[29] \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\" \n",
      "[33] \"1110004E09Rik\"  \"1810007M14Rik\"  \"4932438H23Rik\"  \"Olig2\"         \n",
      "[37] \"Olig1\"          \"Il10rb\"         \"Dnajc28\"        \"Kcne2\"         \n",
      "[41] \"4930563D23Rik\"  \"Kcne1\"          \"Clic6\"          \"Runx1\"         \n",
      "[45] \"mmu-miR-802\"    \"Cbr3\"           \"Dopey2\"         \"Chaf1b\"        \n",
      "[49] \"Cldn14\"         \"Sim2\"           \"Ripply3\"        \"Dscr3\"         \n",
      "[53] \"Kcnj15\"         \"Erg\"            \"Psmg1\"          \"Sh3bgr\"        \n",
      "[57] \"Igsf5\"          \"Itgb2l\"         \"Bace2\"          \"Fam3b\"         \n",
      "[61] \"Mx2\"            \"Tmprss2\"        \"Ripk4\"          \"5830404H04Rik\" \n",
      "[65] \"Zfp295\"        \n",
      "[1] \"OPC\"\n",
      "[1] \"detected\"\n",
      "[1] 59\n",
      " [1] \"Rbm11\"       \"Hspa13\"      \"Nrip1\"       \"Usp25\"       \"Cxadr\"      \n",
      " [6] \"Btg3\"        \"D16Ertd472e\" \"Ncam2\"       \"Mrpl39\"      \"Jam2\"       \n",
      "[11] \"Atp5j\"       \"Gabpa\"       \"App\"         \"Adamts1\"     \"Adamts5\"    \n",
      "[16] \"N6amt1\"      \"Usp16\"       \"Cct8\"        \"Bach1\"       \"Grik1\"      \n",
      "[21] \"Tiam1\"       \"Sod1\"        \"Hunk\"        \"Urb1\"        \"Synj1\"      \n",
      "[26] \"Olig2\"       \"Olig1\"       \"Ifnar2\"      \"Ifnar1\"      \"Ifngr2\"     \n",
      "[31] \"Tmem50b\"     \"Gart\"        \"Son\"         \"Donson\"      \"Cryzl1\"     \n",
      "[36] \"Itsn1\"       \"Atp5o\"       \"Mrps6\"       \"Slc5a3\"      \"Rcan1\"      \n",
      "[41] \"Clic6\"       \"Setd4\"       \"Cbr1\"        \"Cbr3\"        \"Morc3\"      \n",
      "[46] \"Hlcs\"        \"Pigp\"        \"Ttc3\"        \"Dyrk1a\"      \"Kcnj6\"      \n",
      "[51] \"Ets2\"        \"Psmg1\"       \"Brwd1\"       \"Hmgn1\"       \"Wrb\"        \n",
      "[56] \"Lca5l\"       \"B3galt5\"     \"Dscam\"       \"Prdm15\"     \n",
      "[1] \"not detected\"\n",
      "[1] 55\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      " [9] \"Cyyr1\"          \"Zfp294\"         \"Rwdd2b\"         \"Orf63\"         \n",
      "[13] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[17] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[21] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[25] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[29] \"1810007M14Rik\"  \"4932438H23Rik\"  \"Il10rb\"         \"Dnajc28\"       \n",
      "[33] \"Kcne2\"          \"4930563D23Rik\"  \"Kcne1\"          \"Runx1\"         \n",
      "[37] \"mmu-miR-802\"    \"Dopey2\"         \"Chaf1b\"         \"Cldn14\"        \n",
      "[41] \"Sim2\"           \"Ripply3\"        \"Dscr3\"          \"Kcnj15\"        \n",
      "[45] \"Erg\"            \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"        \n",
      "[49] \"Bace2\"          \"Fam3b\"          \"Mx2\"            \"Tmprss2\"       \n",
      "[53] \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Oligodendrocyte\"\n",
      "[1] \"detected\"\n",
      "[1] 46\n",
      " [1] \"Rbm11\"       \"Hspa13\"      \"Nrip1\"       \"Usp25\"       \"D16Ertd472e\"\n",
      " [6] \"Ncam2\"       \"Mrpl39\"      \"Atp5j\"       \"Gabpa\"       \"App\"        \n",
      "[11] \"Adamts1\"     \"Usp16\"       \"Cct8\"        \"Bach1\"       \"Grik1\"      \n",
      "[16] \"Sod1\"        \"Hunk\"        \"Urb1\"        \"Synj1\"       \"Olig2\"      \n",
      "[21] \"Olig1\"       \"Ifnar2\"      \"Ifnar1\"      \"Tmem50b\"     \"Gart\"       \n",
      "[26] \"Son\"         \"Cryzl1\"      \"Itsn1\"       \"Atp5o\"       \"Mrps6\"      \n",
      "[31] \"Slc5a3\"      \"Rcan1\"       \"Setd4\"       \"Cbr1\"        \"Morc3\"      \n",
      "[36] \"Cldn14\"      \"Hlcs\"        \"Pigp\"        \"Ttc3\"        \"Dyrk1a\"     \n",
      "[41] \"Brwd1\"       \"Hmgn1\"       \"Wrb\"         \"B3galt5\"     \"Dscam\"      \n",
      "[46] \"Prdm15\"     \n",
      "[1] \"not detected\"\n",
      "[1] 68\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Cxadr\"          \"Btg3\"           \"Chodl\"         \n",
      " [9] \"Prss7\"          \"mmu-miR-155\"    \"Jam2\"           \"Cyyr1\"         \n",
      "[13] \"Adamts5\"        \"N6amt1\"         \"Zfp294\"         \"Rwdd2b\"        \n",
      "[17] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[21] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[25] \"Krtap16-7\"      \"Krtap8-1\"       \"Tiam1\"          \"Krtap16-4\"     \n",
      "[29] \"Krtap8-2\"       \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"          \n",
      "[33] \"4931408A02Rik\"  \"1110004E09Rik\"  \"1810007M14Rik\"  \"4932438H23Rik\" \n",
      "[37] \"Il10rb\"         \"Ifngr2\"         \"Dnajc28\"        \"Donson\"        \n",
      "[41] \"Kcne2\"          \"4930563D23Rik\"  \"Kcne1\"          \"Clic6\"         \n",
      "[45] \"Runx1\"          \"mmu-miR-802\"    \"Cbr3\"           \"Dopey2\"        \n",
      "[49] \"Chaf1b\"         \"Sim2\"           \"Ripply3\"        \"Dscr3\"         \n",
      "[53] \"Kcnj6\"          \"Kcnj15\"         \"Erg\"            \"Ets2\"          \n",
      "[57] \"Psmg1\"          \"Lca5l\"          \"Sh3bgr\"         \"Igsf5\"         \n",
      "[61] \"Itgb2l\"         \"Bace2\"          \"Fam3b\"          \"Mx2\"           \n",
      "[65] \"Tmprss2\"        \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Astrocyte\"\n",
      "[1] \"detected\"\n",
      "[1] 61\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Nrip1\"         \"Usp25\"        \n",
      " [5] \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"   \"Ncam2\"        \n",
      " [9] \"Mrpl39\"        \"Jam2\"          \"Atp5j\"         \"Gabpa\"        \n",
      "[13] \"App\"           \"Adamts1\"       \"N6amt1\"        \"Usp16\"        \n",
      "[17] \"Cct8\"          \"Bach1\"         \"Grik1\"         \"Tiam1\"        \n",
      "[21] \"Sod1\"          \"Hunk\"          \"Urb1\"          \"Synj1\"        \n",
      "[25] \"4932438H23Rik\" \"Olig2\"         \"Olig1\"         \"Ifnar2\"       \n",
      "[29] \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"        \"Tmem50b\"      \n",
      "[33] \"Dnajc28\"       \"Gart\"          \"Son\"           \"Donson\"       \n",
      "[37] \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"         \"Mrps6\"        \n",
      "[41] \"Slc5a3\"        \"Rcan1\"         \"Clic6\"         \"Setd4\"        \n",
      "[45] \"Cbr1\"          \"Cbr3\"          \"Morc3\"         \"Hlcs\"         \n",
      "[49] \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"        \"Kcnj6\"        \n",
      "[53] \"Ets2\"          \"Psmg1\"         \"Brwd1\"         \"Hmgn1\"        \n",
      "[57] \"Wrb\"           \"Lca5l\"         \"B3galt5\"       \"Dscam\"        \n",
      "[61] \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 53\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      " [9] \"Cyyr1\"          \"Adamts5\"        \"Zfp294\"         \"Rwdd2b\"        \n",
      "[13] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[17] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[21] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[25] \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\" \n",
      "[29] \"1110004E09Rik\"  \"1810007M14Rik\"  \"Kcne2\"          \"4930563D23Rik\" \n",
      "[33] \"Kcne1\"          \"Runx1\"          \"mmu-miR-802\"    \"Dopey2\"        \n",
      "[37] \"Chaf1b\"         \"Cldn14\"         \"Sim2\"           \"Ripply3\"       \n",
      "[41] \"Dscr3\"          \"Kcnj15\"         \"Erg\"            \"Sh3bgr\"        \n",
      "[45] \"Igsf5\"          \"Itgb2l\"         \"Bace2\"          \"Fam3b\"         \n",
      "[49] \"Mx2\"            \"Tmprss2\"        \"Ripk4\"          \"5830404H04Rik\" \n",
      "[53] \"Zfp295\"        \n",
      "[1] \"Microglia\"\n",
      "[1] \"detected\"\n",
      "[1] 38\n",
      " [1] \"Samsn1\"  \"Nrip1\"   \"Usp25\"   \"Ncam2\"   \"Jam2\"    \"Atp5j\"   \"App\"    \n",
      " [8] \"Usp16\"   \"Cct8\"    \"Bach1\"   \"Grik1\"   \"Tiam1\"   \"Sod1\"    \"Synj1\"  \n",
      "[15] \"Ifnar2\"  \"Il10rb\"  \"Ifnar1\"  \"Ifngr2\"  \"Tmem50b\" \"Gart\"    \"Son\"    \n",
      "[22] \"Cryzl1\"  \"Itsn1\"   \"Atp5o\"   \"Mrps6\"   \"Rcan1\"   \"Runx1\"   \"Setd4\"  \n",
      "[29] \"Morc3\"   \"Hlcs\"    \"Pigp\"    \"Ttc3\"    \"Dyrk1a\"  \"Brwd1\"   \"Hmgn1\"  \n",
      "[36] \"B3galt5\" \"Dscam\"   \"Prdm15\" \n",
      "[1] \"not detected\"\n",
      "[1] 76\n",
      " [1] \"Lipi\"           \"Rbm11\"          \"Hspa13\"         \"mmu-miR-99a\"   \n",
      " [5] \"mmu-let-7c-1\"   \"mmu-miR-125b-2\" \"Cxadr\"          \"Btg3\"          \n",
      " [9] \"D16Ertd472e\"    \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      "[13] \"Mrpl39\"         \"Gabpa\"          \"Cyyr1\"          \"Adamts1\"       \n",
      "[17] \"Adamts5\"        \"N6amt1\"         \"Zfp294\"         \"Rwdd2b\"        \n",
      "[21] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[25] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[29] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[33] \"Sfrs15\"         \"Hunk\"           \"2610039C10Rik\"  \"Mrap\"          \n",
      "[37] \"Urb1\"           \"4931408A02Rik\"  \"1110004E09Rik\"  \"1810007M14Rik\" \n",
      "[41] \"4932438H23Rik\"  \"Olig2\"          \"Olig1\"          \"Dnajc28\"       \n",
      "[45] \"Donson\"         \"Slc5a3\"         \"Kcne2\"          \"4930563D23Rik\" \n",
      "[49] \"Kcne1\"          \"Clic6\"          \"mmu-miR-802\"    \"Cbr1\"          \n",
      "[53] \"Cbr3\"           \"Dopey2\"         \"Chaf1b\"         \"Cldn14\"        \n",
      "[57] \"Sim2\"           \"Ripply3\"        \"Dscr3\"          \"Kcnj6\"         \n",
      "[61] \"Kcnj15\"         \"Erg\"            \"Ets2\"           \"Psmg1\"         \n",
      "[65] \"Wrb\"            \"Lca5l\"          \"Sh3bgr\"         \"Igsf5\"         \n",
      "[69] \"Itgb2l\"         \"Bace2\"          \"Fam3b\"          \"Mx2\"           \n",
      "[73] \"Tmprss2\"        \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "       GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
      "Lipi          nd            nd   nd  nd              nd        nd        nd\n",
      "Rbm11         No            No   No  No              No        No        nd\n",
      "Hspa13        No            No   No  No              No        No        nd\n",
      "Samsn1      <NA>            No   nd  nd              nd        nd        No\n",
      "Nrip1         No            No   No  No              No        No        No\n",
      "Usp25         No            No   No  No              No        No        No\n",
      "       GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
      "Lipi          nd            nd   nd  nd              nd        nd        nd\n",
      "Rbm11         No            No   No  No              No        No        nd\n",
      "Hspa13        No            No   No  No              No        No        nd\n",
      "Samsn1        No            No   nd  nd              nd        nd        No\n",
      "Nrip1         No            No   No  No              No        No        No\n",
      "Usp25         No            No   No  No              No        No        No\n",
      "[1] \"initial dims of plotMtx\"\n",
      "[1] 114   7\n",
      "[1] \"dimensions of pct exp matrix\"\n",
      "[1] 90 14\n",
      "[1] \"dim of plotMtx after subsetting for detected PctExp genes\"\n",
      "[1] 90  7\n",
      "       Astrocyte_2N_yng Astrocyte_Dp16_yng BFCN_2N_yng BFCN_Dp16_yng\n",
      "Rbm11         1.1308562          2.9826015  16.4556962     21.653543\n",
      "Hspa13        7.1082391          9.8591549  19.6202532     23.622047\n",
      "Samsn1        0.2692515          0.5799503   0.6329114      1.574803\n",
      "Nrip1        15.4011847         23.9436620  58.8607595     68.503937\n",
      "Usp25        17.3397954         23.3637117  44.9367089     52.755906\n",
      "Cxadr         6.4620355         11.5161558  28.4810127     43.700787\n",
      "       GABAergic_2N_yng GABAergic_Dp16_yng Glutamatergic_2N_yng\n",
      "Rbm11          4.341711          6.3872472             7.050766\n",
      "Hspa13        11.954993         14.8240525            16.599517\n",
      "Samsn1         0.214028          0.3470151             1.329573\n",
      "Nrip1         20.956399         25.1640189            32.634972\n",
      "Usp25         25.542714         31.3126932            42.707494\n",
      "Cxadr         22.742005         27.4413056            34.649476\n",
      "       Glutamatergic_Dp16_yng Microglia_2N_yng Microglia_Dp16_yng\n",
      "Rbm11               6.9778189        0.3780718          0.0000000\n",
      "Hspa13             17.3290203        2.4574669          1.5901060\n",
      "Samsn1              0.5545287       12.0982987         10.0706714\n",
      "Nrip1              24.4916821       38.3742911         40.7243816\n",
      "Usp25              35.4436229       10.7750473          9.9823322\n",
      "Cxadr              28.8817006        1.1342155          0.5300353\n",
      "       Oligodendrocyte_2N_yng Oligodendrocyte_Dp16_yng OPC_2N_yng OPC_Dp16_yng\n",
      "Rbm11               0.9341200                1.2663399  5.9748428    8.0617496\n",
      "Hspa13              1.2291052                1.4705882 10.0628931   15.9519726\n",
      "Samsn1              0.0000000                0.0000000  0.1572327    0.3430532\n",
      "Nrip1               8.7020649               11.9689542 20.9119497   27.4442539\n",
      "Usp25              14.3067847               16.3398693 21.0691824   29.3310463\n",
      "Cxadr               0.2949853                0.2042484 15.4088050   23.1560892\n",
      "[1] \"keep genes\"\n",
      " [1] \"4932438H23Rik\" \"Adamts1\"       \"Adamts5\"       \"App\"          \n",
      " [5] \"Atp5j\"         \"Atp5o\"         \"B3galt5\"       \"Bach1\"        \n",
      " [9] \"Brwd1\"         \"Btg3\"          \"Cbr1\"          \"Cbr3\"         \n",
      "[13] \"Cct8\"          \"Cldn14\"        \"Clic6\"         \"Cryzl1\"       \n",
      "[17] \"Cxadr\"         \"Cyyr1\"         \"D16Ertd472e\"   \"Dnajc28\"      \n",
      "[21] \"Donson\"        \"Dscam\"         \"Dyrk1a\"        \"Ets2\"         \n",
      "[25] \"Gabpa\"         \"Gart\"          \"Grik1\"         \"Hlcs\"         \n",
      "[29] \"Hmgn1\"         \"Hspa13\"        \"Hunk\"          \"Ifnar1\"       \n",
      "[33] \"Ifnar2\"        \"Ifngr2\"        \"Igsf5\"         \"Il10rb\"       \n",
      "[37] \"Itsn1\"         \"Jam2\"          \"Kcnj6\"         \"Lca5l\"        \n",
      "[41] \"Morc3\"         \"Mrpl39\"        \"Mrps6\"         \"N6amt1\"       \n",
      "[45] \"Ncam2\"         \"Nrip1\"         \"Olig1\"         \"Olig2\"        \n",
      "[49] \"Pigp\"          \"Prdm15\"        \"Psmg1\"         \"Rbm11\"        \n",
      "[53] \"Rcan1\"         \"Ripk4\"         \"Runx1\"         \"Rwdd2b\"       \n",
      "[57] \"Samsn1\"        \"Setd4\"         \"Sh3bgr\"        \"Slc5a3\"       \n",
      "[61] \"Sod1\"          \"Son\"           \"Synj1\"         \"Tiam1\"        \n",
      "[65] \"Tmem50b\"       \"Ttc3\"          \"Urb1\"          \"Usp16\"        \n",
      "[69] \"Usp25\"         \"Wrb\"          \n",
      "[1] 70\n",
      "[1] \"subset plotMtx for passing pctExp genes\"\n",
      "[1] 70  7\n",
      "[1] 70  7\n",
      "        Astrocyte Microglia Oligodendrocyte       OPC      BFCN GABAergic\n",
      "Rbm11  1.14492164 0.0000000       0.6135870 0.5848907 0.8074042 0.6417304\n",
      "Hspa13 0.09550896 0.0000000       0.4121054 0.6855615 0.4989820 0.4111958\n",
      "Samsn1 0.00000000 0.3569114       0.0000000 0.0000000 0.0000000 0.6248365\n",
      "Nrip1  0.38881287 0.8206349       0.7282484 0.3894978 0.4992387 0.3286375\n",
      "Usp25  0.08381887 0.6907387       0.4313141 0.4399321 0.2085924 0.3789779\n",
      "Cxadr  0.60105936 0.0000000       0.0000000 0.6259466 0.9153067 0.3671181\n",
      "       Glutamatergic\n",
      "Rbm11      0.4315004\n",
      "Hspa13     0.2825875\n",
      "Samsn1    -0.3178932\n",
      "Nrip1     -0.1537117\n",
      "Usp25      0.1490267\n",
      "Cxadr      0.1655907\n",
      "[1] 70  7\n",
      "       Astrocyte Microglia Oligodendrocyte OPC BFCN GABAergic Glutamatergic\n",
      "Rbm11         No        nd              --  No   No        No            No\n",
      "Hspa13        No        nd              --  No   No        No            No\n",
      "Samsn1        nd        No              nd  nd   nd        --            --\n",
      "Nrip1         No        No              No  No   No        No            No\n",
      "Usp25         No        No              No  No   No        No            No\n",
      "Cxadr         No        nd              nd  No   No        No            No\n",
      "[1] \"DONE: Dp16_yng-2N_yng\"\n",
      "[1] \"STARTING: Dp16_old-2N_old\"\n",
      "[1] \"GABAergic\"\n",
      "[1] \"detected\"\n",
      "[1] 75\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 39\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Fam3b\"          \"Mx2\"           \n",
      "[37] \"Tmprss2\"        \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Glutamatergic\"\n",
      "[1] \"detected\"\n",
      "[1] 67\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Nrip1\"         \"Usp25\"        \n",
      " [5] \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"   \"Chodl\"        \n",
      " [9] \"Ncam2\"         \"Mrpl39\"        \"Jam2\"          \"Atp5j\"        \n",
      "[13] \"Gabpa\"         \"App\"           \"Cyyr1\"         \"Adamts1\"      \n",
      "[17] \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"        \"Usp16\"        \n",
      "[21] \"Cct8\"          \"Bach1\"         \"Grik1\"         \"Tiam1\"        \n",
      "[25] \"Sod1\"          \"Hunk\"          \"Urb1\"          \"Synj1\"        \n",
      "[29] \"4932438H23Rik\" \"Olig1\"         \"Ifnar2\"        \"Il10rb\"       \n",
      "[33] \"Ifnar1\"        \"Ifngr2\"        \"Tmem50b\"       \"Dnajc28\"      \n",
      "[37] \"Gart\"          \"Son\"           \"Donson\"        \"Cryzl1\"       \n",
      "[41] \"Itsn1\"         \"Atp5o\"         \"Mrps6\"         \"Slc5a3\"       \n",
      "[45] \"Rcan1\"         \"Clic6\"         \"Runx1\"         \"Setd4\"        \n",
      "[49] \"Cbr1\"          \"Cbr3\"          \"Morc3\"         \"Hlcs\"         \n",
      "[53] \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"        \"Kcnj6\"        \n",
      "[57] \"Ets2\"          \"Psmg1\"         \"Brwd1\"         \"Hmgn1\"        \n",
      "[61] \"Wrb\"           \"Lca5l\"         \"B3galt5\"       \"Dscam\"        \n",
      "[65] \"Bace2\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 47\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"        \n",
      " [9] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[13] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[17] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[21] \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\" \n",
      "[25] \"1110004E09Rik\"  \"1810007M14Rik\"  \"Olig2\"          \"Kcne2\"         \n",
      "[29] \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"    \"Dopey2\"        \n",
      "[33] \"Chaf1b\"         \"Cldn14\"         \"Sim2\"           \"Ripply3\"       \n",
      "[37] \"Dscr3\"          \"Kcnj15\"         \"Erg\"            \"Sh3bgr\"        \n",
      "[41] \"Igsf5\"          \"Itgb2l\"         \"Fam3b\"          \"Mx2\"           \n",
      "[45] \"Tmprss2\"        \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"BFCN\"\n",
      "[1] \"detected\"\n",
      "[1] 45\n",
      " [1] \"Rbm11\"   \"Hspa13\"  \"Nrip1\"   \"Usp25\"   \"Cxadr\"   \"Ncam2\"   \"Atp5j\"  \n",
      " [8] \"Gabpa\"   \"App\"     \"Usp16\"   \"Cct8\"    \"Bach1\"   \"Grik1\"   \"Tiam1\"  \n",
      "[15] \"Sod1\"    \"Hunk\"    \"Synj1\"   \"Ifnar2\"  \"Ifnar1\"  \"Ifngr2\"  \"Tmem50b\"\n",
      "[22] \"Gart\"    \"Son\"     \"Donson\"  \"Cryzl1\"  \"Itsn1\"   \"Atp5o\"   \"Mrps6\"  \n",
      "[29] \"Slc5a3\"  \"Rcan1\"   \"Setd4\"   \"Cbr1\"    \"Morc3\"   \"Hlcs\"    \"Pigp\"   \n",
      "[36] \"Ttc3\"    \"Dyrk1a\"  \"Kcnj6\"   \"Brwd1\"   \"Hmgn1\"   \"Wrb\"     \"Lca5l\"  \n",
      "[43] \"B3galt5\" \"Dscam\"   \"Prdm15\" \n",
      "[1] \"not detected\"\n",
      "[1] 69\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Btg3\"           \"D16Ertd472e\"    \"Chodl\"         \n",
      " [9] \"Prss7\"          \"mmu-miR-155\"    \"Mrpl39\"         \"Jam2\"          \n",
      "[13] \"Cyyr1\"          \"Adamts1\"        \"Adamts5\"        \"N6amt1\"        \n",
      "[17] \"Zfp294\"         \"Rwdd2b\"         \"Orf63\"          \"Cldn17\"        \n",
      "[21] \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"      \"Krtap13-1\"     \n",
      "[25] \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"      \"Krtap8-1\"      \n",
      "[29] \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"         \"2610039C10Rik\" \n",
      "[33] \"Mrap\"           \"Urb1\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[37] \"1810007M14Rik\"  \"4932438H23Rik\"  \"Olig2\"          \"Olig1\"         \n",
      "[41] \"Il10rb\"         \"Dnajc28\"        \"Kcne2\"          \"4930563D23Rik\" \n",
      "[45] \"Kcne1\"          \"Clic6\"          \"Runx1\"          \"mmu-miR-802\"   \n",
      "[49] \"Cbr3\"           \"Dopey2\"         \"Chaf1b\"         \"Cldn14\"        \n",
      "[53] \"Sim2\"           \"Ripply3\"        \"Dscr3\"          \"Kcnj15\"        \n",
      "[57] \"Erg\"            \"Ets2\"           \"Psmg1\"          \"Sh3bgr\"        \n",
      "[61] \"Igsf5\"          \"Itgb2l\"         \"Bace2\"          \"Fam3b\"         \n",
      "[65] \"Mx2\"            \"Tmprss2\"        \"Ripk4\"          \"5830404H04Rik\" \n",
      "[69] \"Zfp295\"        \n",
      "[1] \"OPC\"\n",
      "[1] \"detected\"\n",
      "[1] 56\n",
      " [1] \"Rbm11\"       \"Hspa13\"      \"Nrip1\"       \"Usp25\"       \"Cxadr\"      \n",
      " [6] \"Btg3\"        \"D16Ertd472e\" \"Ncam2\"       \"Jam2\"        \"Atp5j\"      \n",
      "[11] \"Gabpa\"       \"App\"         \"Adamts5\"     \"N6amt1\"      \"Usp16\"      \n",
      "[16] \"Cct8\"        \"Bach1\"       \"Grik1\"       \"Tiam1\"       \"Sod1\"       \n",
      "[21] \"Hunk\"        \"Urb1\"        \"Synj1\"       \"Olig2\"       \"Olig1\"      \n",
      "[26] \"Ifnar2\"      \"Ifnar1\"      \"Ifngr2\"      \"Tmem50b\"     \"Gart\"       \n",
      "[31] \"Son\"         \"Donson\"      \"Cryzl1\"      \"Itsn1\"       \"Atp5o\"      \n",
      "[36] \"Mrps6\"       \"Slc5a3\"      \"Rcan1\"       \"Clic6\"       \"Setd4\"      \n",
      "[41] \"Cbr1\"        \"Cbr3\"        \"Morc3\"       \"Hlcs\"        \"Pigp\"       \n",
      "[46] \"Ttc3\"        \"Dyrk1a\"      \"Kcnj6\"       \"Ets2\"        \"Brwd1\"      \n",
      "[51] \"Hmgn1\"       \"Wrb\"         \"Lca5l\"       \"B3galt5\"     \"Dscam\"      \n",
      "[56] \"Prdm15\"     \n",
      "[1] \"not detected\"\n",
      "[1] 58\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      " [9] \"Mrpl39\"         \"Cyyr1\"          \"Adamts1\"        \"Zfp294\"        \n",
      "[13] \"Rwdd2b\"         \"Orf63\"          \"Cldn17\"         \"Cldn8\"         \n",
      "[17] \"Gm312\"          \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"       \n",
      "[21] \"Krtap16\"        \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"     \n",
      "[25] \"Krtap8-2\"       \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"          \n",
      "[29] \"4931408A02Rik\"  \"1110004E09Rik\"  \"1810007M14Rik\"  \"4932438H23Rik\" \n",
      "[33] \"Il10rb\"         \"Dnajc28\"        \"Kcne2\"          \"4930563D23Rik\" \n",
      "[37] \"Kcne1\"          \"Runx1\"          \"mmu-miR-802\"    \"Dopey2\"        \n",
      "[41] \"Chaf1b\"         \"Cldn14\"         \"Sim2\"           \"Ripply3\"       \n",
      "[45] \"Dscr3\"          \"Kcnj15\"         \"Erg\"            \"Psmg1\"         \n",
      "[49] \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"         \"Bace2\"         \n",
      "[53] \"Fam3b\"          \"Mx2\"            \"Tmprss2\"        \"Ripk4\"         \n",
      "[57] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Oligodendrocyte\"\n",
      "[1] \"detected\"\n",
      "[1] 55\n",
      " [1] \"Rbm11\"       \"Hspa13\"      \"Nrip1\"       \"Usp25\"       \"Cxadr\"      \n",
      " [6] \"Btg3\"        \"D16Ertd472e\" \"Ncam2\"       \"Mrpl39\"      \"Jam2\"       \n",
      "[11] \"Atp5j\"       \"Gabpa\"       \"App\"         \"Adamts1\"     \"N6amt1\"     \n",
      "[16] \"Usp16\"       \"Cct8\"        \"Bach1\"       \"Grik1\"       \"Tiam1\"      \n",
      "[21] \"Sod1\"        \"Hunk\"        \"Urb1\"        \"Synj1\"       \"Olig2\"      \n",
      "[26] \"Olig1\"       \"Ifnar2\"      \"Ifnar1\"      \"Tmem50b\"     \"Gart\"       \n",
      "[31] \"Son\"         \"Donson\"      \"Cryzl1\"      \"Itsn1\"       \"Atp5o\"      \n",
      "[36] \"Mrps6\"       \"Slc5a3\"      \"Rcan1\"       \"Setd4\"       \"Cbr1\"       \n",
      "[41] \"Morc3\"       \"Cldn14\"      \"Hlcs\"        \"Pigp\"        \"Ttc3\"       \n",
      "[46] \"Dyrk1a\"      \"Kcnj6\"       \"Psmg1\"       \"Brwd1\"       \"Hmgn1\"      \n",
      "[51] \"Wrb\"         \"Lca5l\"       \"B3galt5\"     \"Dscam\"       \"Prdm15\"     \n",
      "[1] \"not detected\"\n",
      "[1] 59\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      " [9] \"Cyyr1\"          \"Adamts5\"        \"Zfp294\"         \"Rwdd2b\"        \n",
      "[13] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[17] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[21] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[25] \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\" \n",
      "[29] \"1110004E09Rik\"  \"1810007M14Rik\"  \"4932438H23Rik\"  \"Il10rb\"        \n",
      "[33] \"Ifngr2\"         \"Dnajc28\"        \"Kcne2\"          \"4930563D23Rik\" \n",
      "[37] \"Kcne1\"          \"Clic6\"          \"Runx1\"          \"mmu-miR-802\"   \n",
      "[41] \"Cbr3\"           \"Dopey2\"         \"Chaf1b\"         \"Sim2\"          \n",
      "[45] \"Ripply3\"        \"Dscr3\"          \"Kcnj15\"         \"Erg\"           \n",
      "[49] \"Ets2\"           \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"        \n",
      "[53] \"Bace2\"          \"Fam3b\"          \"Mx2\"            \"Tmprss2\"       \n",
      "[57] \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Astrocyte\"\n",
      "[1] \"detected\"\n",
      "[1] 57\n",
      " [1] \"Hspa13\"        \"Nrip1\"         \"Usp25\"         \"Cxadr\"        \n",
      " [5] \"Btg3\"          \"D16Ertd472e\"   \"Ncam2\"         \"Mrpl39\"       \n",
      " [9] \"Jam2\"          \"Atp5j\"         \"Gabpa\"         \"App\"          \n",
      "[13] \"N6amt1\"        \"Usp16\"         \"Cct8\"          \"Bach1\"        \n",
      "[17] \"Grik1\"         \"Tiam1\"         \"Sod1\"          \"Hunk\"         \n",
      "[21] \"Urb1\"          \"Synj1\"         \"4932438H23Rik\" \"Olig2\"        \n",
      "[25] \"Olig1\"         \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"       \n",
      "[29] \"Ifngr2\"        \"Tmem50b\"       \"Gart\"          \"Son\"          \n",
      "[33] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[37] \"Mrps6\"         \"Slc5a3\"        \"Rcan1\"         \"Clic6\"        \n",
      "[41] \"Setd4\"         \"Cbr1\"          \"Cbr3\"          \"Morc3\"        \n",
      "[45] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[49] \"Kcnj6\"         \"Ets2\"          \"Brwd1\"         \"Hmgn1\"        \n",
      "[53] \"Wrb\"           \"Lca5l\"         \"B3galt5\"       \"Dscam\"        \n",
      "[57] \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 57\n",
      " [1] \"Lipi\"           \"Rbm11\"          \"Samsn1\"         \"mmu-miR-99a\"   \n",
      " [5] \"mmu-let-7c-1\"   \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"         \n",
      " [9] \"mmu-miR-155\"    \"Cyyr1\"          \"Adamts1\"        \"Adamts5\"       \n",
      "[13] \"Zfp294\"         \"Rwdd2b\"         \"Orf63\"          \"Cldn17\"        \n",
      "[17] \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"      \"Krtap13-1\"     \n",
      "[21] \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"      \"Krtap8-1\"      \n",
      "[25] \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"         \"2610039C10Rik\" \n",
      "[29] \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\"  \"1810007M14Rik\" \n",
      "[33] \"Dnajc28\"        \"Kcne2\"          \"4930563D23Rik\"  \"Kcne1\"         \n",
      "[37] \"Runx1\"          \"mmu-miR-802\"    \"Dopey2\"         \"Chaf1b\"        \n",
      "[41] \"Cldn14\"         \"Sim2\"           \"Ripply3\"        \"Dscr3\"         \n",
      "[45] \"Kcnj15\"         \"Erg\"            \"Psmg1\"          \"Sh3bgr\"        \n",
      "[49] \"Igsf5\"          \"Itgb2l\"         \"Bace2\"          \"Fam3b\"         \n",
      "[53] \"Mx2\"            \"Tmprss2\"        \"Ripk4\"          \"5830404H04Rik\" \n",
      "[57] \"Zfp295\"        \n",
      "[1] \"Microglia\"\n",
      "[1] \"detected\"\n",
      "[1] 35\n",
      " [1] \"Samsn1\"  \"Nrip1\"   \"Usp25\"   \"Ncam2\"   \"Jam2\"    \"Atp5j\"   \"Gabpa\"  \n",
      " [8] \"App\"     \"Usp16\"   \"Bach1\"   \"Grik1\"   \"Tiam1\"   \"Sod1\"    \"Synj1\"  \n",
      "[15] \"Ifnar2\"  \"Il10rb\"  \"Ifnar1\"  \"Ifngr2\"  \"Tmem50b\" \"Gart\"    \"Son\"    \n",
      "[22] \"Cryzl1\"  \"Itsn1\"   \"Rcan1\"   \"Runx1\"   \"Setd4\"   \"Morc3\"   \"Hlcs\"   \n",
      "[29] \"Pigp\"    \"Ttc3\"    \"Dyrk1a\"  \"Brwd1\"   \"B3galt5\" \"Dscam\"   \"Prdm15\" \n",
      "[1] \"not detected\"\n",
      "[1] 79\n",
      " [1] \"Lipi\"           \"Rbm11\"          \"Hspa13\"         \"mmu-miR-99a\"   \n",
      " [5] \"mmu-let-7c-1\"   \"mmu-miR-125b-2\" \"Cxadr\"          \"Btg3\"          \n",
      " [9] \"D16Ertd472e\"    \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      "[13] \"Mrpl39\"         \"Cyyr1\"          \"Adamts1\"        \"Adamts5\"       \n",
      "[17] \"N6amt1\"         \"Zfp294\"         \"Rwdd2b\"         \"Cct8\"          \n",
      "[21] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[25] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[29] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[33] \"Sfrs15\"         \"Hunk\"           \"2610039C10Rik\"  \"Mrap\"          \n",
      "[37] \"Urb1\"           \"4931408A02Rik\"  \"1110004E09Rik\"  \"1810007M14Rik\" \n",
      "[41] \"4932438H23Rik\"  \"Olig2\"          \"Olig1\"          \"Dnajc28\"       \n",
      "[45] \"Donson\"         \"Atp5o\"          \"Mrps6\"          \"Slc5a3\"        \n",
      "[49] \"Kcne2\"          \"4930563D23Rik\"  \"Kcne1\"          \"Clic6\"         \n",
      "[53] \"mmu-miR-802\"    \"Cbr1\"           \"Cbr3\"           \"Dopey2\"        \n",
      "[57] \"Chaf1b\"         \"Cldn14\"         \"Sim2\"           \"Ripply3\"       \n",
      "[61] \"Dscr3\"          \"Kcnj6\"          \"Kcnj15\"         \"Erg\"           \n",
      "[65] \"Ets2\"           \"Psmg1\"          \"Hmgn1\"          \"Wrb\"           \n",
      "[69] \"Lca5l\"          \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"        \n",
      "[73] \"Bace2\"          \"Fam3b\"          \"Mx2\"            \"Tmprss2\"       \n",
      "[77] \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "       GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
      "Lipi          nd            nd   nd  nd              nd        nd        nd\n",
      "Rbm11        Yes           Yes <NA>  No              No        nd        nd\n",
      "Hspa13        No            No <NA>  No              No        No        nd\n",
      "Samsn1      <NA>            nd   nd  nd              nd        nd      <NA>\n",
      "Nrip1        Yes            No   No  No              No        No        No\n",
      "Usp25        Yes            No   No  No              No        No      <NA>\n",
      "       GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
      "Lipi          nd            nd   nd  nd              nd        nd        nd\n",
      "Rbm11        Yes           Yes   No  No              No        nd        nd\n",
      "Hspa13        No            No   No  No              No        No        nd\n",
      "Samsn1        No            nd   nd  nd              nd        nd        No\n",
      "Nrip1        Yes            No   No  No              No        No        No\n",
      "Usp25        Yes            No   No  No              No        No        No\n",
      "[1] \"initial dims of plotMtx\"\n",
      "[1] 114   7\n",
      "[1] \"dimensions of pct exp matrix\"\n",
      "[1] 90 14\n",
      "[1] \"dim of plotMtx after subsetting for detected PctExp genes\"\n",
      "[1] 90  7\n",
      "       Astrocyte_2N_old Astrocyte_Dp16_old BFCN_2N_old BFCN_Dp16_old\n",
      "Rbm11         0.9247028          3.9556962  10.0000000     25.423729\n",
      "Hspa13        5.1519155         13.9240506  11.8181818     33.050847\n",
      "Samsn1        0.1321004          0.4746835   0.9090909      1.694915\n",
      "Nrip1        10.7661823         32.5949367  49.0909091     68.644068\n",
      "Usp25        11.7569353         34.9683544  40.0000000     62.711864\n",
      "Cxadr         4.5574637         17.0886076  19.0909091     47.457627\n",
      "       GABAergic_2N_old GABAergic_Dp16_old Glutamatergic_2N_old\n",
      "Rbm11         3.2907038          9.1720503            2.7744270\n",
      "Hspa13       10.3283225         17.8850731           11.1379172\n",
      "Samsn1        0.2542817          0.5015301            0.2412545\n",
      "Nrip1        15.8103358         31.8259096           19.5014073\n",
      "Usp25        19.9012789         43.5056103           30.8001608\n",
      "Cxadr        17.0967018         40.8364502           22.3964616\n",
      "       Glutamatergic_Dp16_old Microglia_2N_old Microglia_Dp16_old\n",
      "Rbm11               9.3628809        0.1424501          0.1277139\n",
      "Hspa13             21.1634349        0.4273504          1.7879949\n",
      "Samsn1              0.7202216        7.9772080         15.7088123\n",
      "Nrip1              34.5152355       25.4985755         49.2975734\n",
      "Usp25              45.9279778        7.5498575         18.9016603\n",
      "Cxadr              45.9833795        0.4273504          0.6385696\n",
      "       Oligodendrocyte_2N_old Oligodendrocyte_Dp16_old OPC_2N_old OPC_Dp16_old\n",
      "Rbm11               0.4583652               1.56583630  4.7516199   12.1126761\n",
      "Hspa13              0.9931245               2.84697509  9.0712743   16.3380282\n",
      "Samsn1              0.0000000               0.07117438  0.6479482    0.2816901\n",
      "Nrip1               5.0038197              12.74021352 11.4470842   28.1690141\n",
      "Usp25               9.1673033              21.42348754 11.8790497   39.7183099\n",
      "Cxadr               0.1527884               0.88967972 12.0950324   27.3239437\n",
      "[1] \"keep genes\"\n",
      " [1] \"4932438H23Rik\" \"Adamts1\"       \"Adamts5\"       \"App\"          \n",
      " [5] \"Atp5j\"         \"Atp5o\"         \"B3galt5\"       \"Bace2\"        \n",
      " [9] \"Bach1\"         \"Brwd1\"         \"Btg3\"          \"Cbr1\"         \n",
      "[13] \"Cbr3\"          \"Cct8\"          \"Chodl\"         \"Cldn14\"       \n",
      "[17] \"Clic6\"         \"Cryzl1\"        \"Cxadr\"         \"Cyyr1\"        \n",
      "[21] \"D16Ertd472e\"   \"Dnajc28\"       \"Donson\"        \"Dscam\"        \n",
      "[25] \"Dyrk1a\"        \"Ets2\"          \"Gabpa\"         \"Gart\"         \n",
      "[29] \"Grik1\"         \"Hlcs\"          \"Hmgn1\"         \"Hspa13\"       \n",
      "[33] \"Hunk\"          \"Ifnar1\"        \"Ifnar2\"        \"Ifngr2\"       \n",
      "[37] \"Igsf5\"         \"Il10rb\"        \"Itsn1\"         \"Jam2\"         \n",
      "[41] \"Kcnj6\"         \"Lca5l\"         \"Morc3\"         \"Mrpl39\"       \n",
      "[45] \"Mrps6\"         \"N6amt1\"        \"Ncam2\"         \"Nrip1\"        \n",
      "[49] \"Olig1\"         \"Olig2\"         \"Pigp\"          \"Prdm15\"       \n",
      "[53] \"Psmg1\"         \"Rbm11\"         \"Rcan1\"         \"Ripk4\"        \n",
      "[57] \"Runx1\"         \"Samsn1\"        \"Setd4\"         \"Sh3bgr\"       \n",
      "[61] \"Slc5a3\"        \"Sod1\"          \"Son\"           \"Synj1\"        \n",
      "[65] \"Tiam1\"         \"Tmem50b\"       \"Ttc3\"          \"Urb1\"         \n",
      "[69] \"Usp16\"         \"Usp25\"         \"Wrb\"          \n",
      "[1] 71\n",
      "[1] \"subset plotMtx for passing pctExp genes\"\n",
      "[1] 71  7\n",
      "[1] 71  7\n",
      "       Astrocyte Microglia Oligodendrocyte        OPC      BFCN  GABAergic\n",
      "Rbm11  0.0000000 0.0000000       0.7653082  0.4415870 0.8275922  0.9048050\n",
      "Hspa13 0.1238973 0.0000000       0.6330854 -0.1321392 0.8505856 -0.0354950\n",
      "Samsn1 0.0000000 0.4989901       0.0000000  0.0000000 0.0000000  0.2603709\n",
      "Nrip1  0.6186786 0.6714049       0.7153220  0.6349486 0.2739173  0.6270267\n",
      "Usp25  0.5502641 0.7532597       0.6307620  1.2211080 0.2195635  0.8312173\n",
      "Cxadr  0.9926490 0.0000000       2.0112661  0.5807306 0.9617281  0.9183107\n",
      "       Glutamatergic\n",
      "Rbm11      1.2437874\n",
      "Hspa13     0.2676689\n",
      "Samsn1     0.0000000\n",
      "Nrip1      0.5090615\n",
      "Usp25      0.2818989\n",
      "Cxadr      0.7608214\n",
      "[1] 71  7\n",
      "       Astrocyte Microglia Oligodendrocyte OPC BFCN GABAergic Glutamatergic\n",
      "Rbm11         nd        nd              --  No   No       Yes           Yes\n",
      "Hspa13        No        nd              No  No   No        No            No\n",
      "Samsn1        nd        No              nd  nd   nd        --            nd\n",
      "Nrip1         No        No              No  No   No       Yes            No\n",
      "Usp25         No        No              No  No   No       Yes            No\n",
      "Cxadr         No        nd              --  No   No       Yes            No\n",
      "[1] \"DONE: Dp16_old-2N_old\"\n",
      "[1] \"STARTING: Dp16_old-Dp16_yng\"\n",
      "[1] \"GABAergic\"\n",
      "[1] \"detected\"\n",
      "[1] 76\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Fam3b\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 38\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Mx2\"            \"Tmprss2\"       \n",
      "[37] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Glutamatergic\"\n",
      "[1] \"detected\"\n",
      "[1] 67\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Nrip1\"         \"Usp25\"        \n",
      " [5] \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"   \"Chodl\"        \n",
      " [9] \"Ncam2\"         \"Mrpl39\"        \"Jam2\"          \"Atp5j\"        \n",
      "[13] \"Gabpa\"         \"App\"           \"Cyyr1\"         \"Adamts1\"      \n",
      "[17] \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"        \"Usp16\"        \n",
      "[21] \"Cct8\"          \"Bach1\"         \"Grik1\"         \"Tiam1\"        \n",
      "[25] \"Sod1\"          \"Hunk\"          \"Urb1\"          \"Synj1\"        \n",
      "[29] \"4932438H23Rik\" \"Olig1\"         \"Ifnar2\"        \"Il10rb\"       \n",
      "[33] \"Ifnar1\"        \"Ifngr2\"        \"Tmem50b\"       \"Dnajc28\"      \n",
      "[37] \"Gart\"          \"Son\"           \"Donson\"        \"Cryzl1\"       \n",
      "[41] \"Itsn1\"         \"Atp5o\"         \"Mrps6\"         \"Slc5a3\"       \n",
      "[45] \"Rcan1\"         \"Clic6\"         \"Runx1\"         \"Setd4\"        \n",
      "[49] \"Cbr1\"          \"Cbr3\"          \"Morc3\"         \"Hlcs\"         \n",
      "[53] \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"        \"Kcnj6\"        \n",
      "[57] \"Ets2\"          \"Psmg1\"         \"Brwd1\"         \"Hmgn1\"        \n",
      "[61] \"Wrb\"           \"Lca5l\"         \"B3galt5\"       \"Dscam\"        \n",
      "[65] \"Bace2\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 47\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"        \n",
      " [9] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[13] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[17] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[21] \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\" \n",
      "[25] \"1110004E09Rik\"  \"1810007M14Rik\"  \"Olig2\"          \"Kcne2\"         \n",
      "[29] \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"    \"Dopey2\"        \n",
      "[33] \"Chaf1b\"         \"Cldn14\"         \"Sim2\"           \"Ripply3\"       \n",
      "[37] \"Dscr3\"          \"Kcnj15\"         \"Erg\"            \"Sh3bgr\"        \n",
      "[41] \"Igsf5\"          \"Itgb2l\"         \"Fam3b\"          \"Mx2\"           \n",
      "[45] \"Tmprss2\"        \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"BFCN\"\n",
      "[1] \"detected\"\n",
      "[1] 49\n",
      " [1] \"Rbm11\"   \"Hspa13\"  \"Nrip1\"   \"Usp25\"   \"Cxadr\"   \"Btg3\"    \"Ncam2\"  \n",
      " [8] \"Atp5j\"   \"Gabpa\"   \"App\"     \"Cyyr1\"   \"Usp16\"   \"Cct8\"    \"Bach1\"  \n",
      "[15] \"Grik1\"   \"Tiam1\"   \"Sod1\"    \"Hunk\"    \"Urb1\"    \"Synj1\"   \"Ifnar2\" \n",
      "[22] \"Ifnar1\"  \"Ifngr2\"  \"Tmem50b\" \"Gart\"    \"Son\"     \"Donson\"  \"Cryzl1\" \n",
      "[29] \"Itsn1\"   \"Atp5o\"   \"Mrps6\"   \"Slc5a3\"  \"Rcan1\"   \"Setd4\"   \"Cbr1\"   \n",
      "[36] \"Morc3\"   \"Hlcs\"    \"Pigp\"    \"Ttc3\"    \"Dyrk1a\"  \"Kcnj6\"   \"Ets2\"   \n",
      "[43] \"Brwd1\"   \"Hmgn1\"   \"Wrb\"     \"Lca5l\"   \"B3galt5\" \"Dscam\"   \"Prdm15\" \n",
      "[1] \"not detected\"\n",
      "[1] 65\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"D16Ertd472e\"    \"Chodl\"          \"Prss7\"         \n",
      " [9] \"mmu-miR-155\"    \"Mrpl39\"         \"Jam2\"           \"Adamts1\"       \n",
      "[13] \"Adamts5\"        \"N6amt1\"         \"Zfp294\"         \"Rwdd2b\"        \n",
      "[17] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[21] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[25] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[29] \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\" \n",
      "[33] \"1110004E09Rik\"  \"1810007M14Rik\"  \"4932438H23Rik\"  \"Olig2\"         \n",
      "[37] \"Olig1\"          \"Il10rb\"         \"Dnajc28\"        \"Kcne2\"         \n",
      "[41] \"4930563D23Rik\"  \"Kcne1\"          \"Clic6\"          \"Runx1\"         \n",
      "[45] \"mmu-miR-802\"    \"Cbr3\"           \"Dopey2\"         \"Chaf1b\"        \n",
      "[49] \"Cldn14\"         \"Sim2\"           \"Ripply3\"        \"Dscr3\"         \n",
      "[53] \"Kcnj15\"         \"Erg\"            \"Psmg1\"          \"Sh3bgr\"        \n",
      "[57] \"Igsf5\"          \"Itgb2l\"         \"Bace2\"          \"Fam3b\"         \n",
      "[61] \"Mx2\"            \"Tmprss2\"        \"Ripk4\"          \"5830404H04Rik\" \n",
      "[65] \"Zfp295\"        \n",
      "[1] \"OPC\"\n",
      "[1] \"detected\"\n",
      "[1] 59\n",
      " [1] \"Rbm11\"       \"Hspa13\"      \"Nrip1\"       \"Usp25\"       \"Cxadr\"      \n",
      " [6] \"Btg3\"        \"D16Ertd472e\" \"Ncam2\"       \"Mrpl39\"      \"Jam2\"       \n",
      "[11] \"Atp5j\"       \"Gabpa\"       \"App\"         \"Adamts1\"     \"Adamts5\"    \n",
      "[16] \"N6amt1\"      \"Usp16\"       \"Cct8\"        \"Bach1\"       \"Grik1\"      \n",
      "[21] \"Tiam1\"       \"Sod1\"        \"Hunk\"        \"Urb1\"        \"Synj1\"      \n",
      "[26] \"Olig2\"       \"Olig1\"       \"Ifnar2\"      \"Ifnar1\"      \"Ifngr2\"     \n",
      "[31] \"Tmem50b\"     \"Gart\"        \"Son\"         \"Donson\"      \"Cryzl1\"     \n",
      "[36] \"Itsn1\"       \"Atp5o\"       \"Mrps6\"       \"Slc5a3\"      \"Rcan1\"      \n",
      "[41] \"Clic6\"       \"Setd4\"       \"Cbr1\"        \"Cbr3\"        \"Morc3\"      \n",
      "[46] \"Hlcs\"        \"Pigp\"        \"Ttc3\"        \"Dyrk1a\"      \"Kcnj6\"      \n",
      "[51] \"Ets2\"        \"Psmg1\"       \"Brwd1\"       \"Hmgn1\"       \"Wrb\"        \n",
      "[56] \"Lca5l\"       \"B3galt5\"     \"Dscam\"       \"Prdm15\"     \n",
      "[1] \"not detected\"\n",
      "[1] 55\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      " [9] \"Cyyr1\"          \"Zfp294\"         \"Rwdd2b\"         \"Orf63\"         \n",
      "[13] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[17] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[21] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[25] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[29] \"1810007M14Rik\"  \"4932438H23Rik\"  \"Il10rb\"         \"Dnajc28\"       \n",
      "[33] \"Kcne2\"          \"4930563D23Rik\"  \"Kcne1\"          \"Runx1\"         \n",
      "[37] \"mmu-miR-802\"    \"Dopey2\"         \"Chaf1b\"         \"Cldn14\"        \n",
      "[41] \"Sim2\"           \"Ripply3\"        \"Dscr3\"          \"Kcnj15\"        \n",
      "[45] \"Erg\"            \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"        \n",
      "[49] \"Bace2\"          \"Fam3b\"          \"Mx2\"            \"Tmprss2\"       \n",
      "[53] \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Oligodendrocyte\"\n",
      "[1] \"detected\"\n",
      "[1] 55\n",
      " [1] \"Rbm11\"       \"Hspa13\"      \"Nrip1\"       \"Usp25\"       \"Cxadr\"      \n",
      " [6] \"Btg3\"        \"D16Ertd472e\" \"Ncam2\"       \"Mrpl39\"      \"Jam2\"       \n",
      "[11] \"Atp5j\"       \"Gabpa\"       \"App\"         \"Adamts1\"     \"N6amt1\"     \n",
      "[16] \"Usp16\"       \"Cct8\"        \"Bach1\"       \"Grik1\"       \"Tiam1\"      \n",
      "[21] \"Sod1\"        \"Hunk\"        \"Urb1\"        \"Synj1\"       \"Olig2\"      \n",
      "[26] \"Olig1\"       \"Ifnar2\"      \"Ifnar1\"      \"Tmem50b\"     \"Gart\"       \n",
      "[31] \"Son\"         \"Donson\"      \"Cryzl1\"      \"Itsn1\"       \"Atp5o\"      \n",
      "[36] \"Mrps6\"       \"Slc5a3\"      \"Rcan1\"       \"Setd4\"       \"Cbr1\"       \n",
      "[41] \"Morc3\"       \"Cldn14\"      \"Hlcs\"        \"Pigp\"        \"Ttc3\"       \n",
      "[46] \"Dyrk1a\"      \"Kcnj6\"       \"Psmg1\"       \"Brwd1\"       \"Hmgn1\"      \n",
      "[51] \"Wrb\"         \"Lca5l\"       \"B3galt5\"     \"Dscam\"       \"Prdm15\"     \n",
      "[1] \"not detected\"\n",
      "[1] 59\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      " [9] \"Cyyr1\"          \"Adamts5\"        \"Zfp294\"         \"Rwdd2b\"        \n",
      "[13] \"Orf63\"          \"Cldn17\"         \"Cldn8\"          \"Gm312\"         \n",
      "[17] \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"       \n",
      "[21] \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"      \n",
      "[25] \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\" \n",
      "[29] \"1110004E09Rik\"  \"1810007M14Rik\"  \"4932438H23Rik\"  \"Il10rb\"        \n",
      "[33] \"Ifngr2\"         \"Dnajc28\"        \"Kcne2\"          \"4930563D23Rik\" \n",
      "[37] \"Kcne1\"          \"Clic6\"          \"Runx1\"          \"mmu-miR-802\"   \n",
      "[41] \"Cbr3\"           \"Dopey2\"         \"Chaf1b\"         \"Sim2\"          \n",
      "[45] \"Ripply3\"        \"Dscr3\"          \"Kcnj15\"         \"Erg\"           \n",
      "[49] \"Ets2\"           \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"        \n",
      "[53] \"Bace2\"          \"Fam3b\"          \"Mx2\"            \"Tmprss2\"       \n",
      "[57] \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Astrocyte\"\n",
      "[1] \"detected\"\n",
      "[1] 60\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Nrip1\"         \"Usp25\"        \n",
      " [5] \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"   \"Ncam2\"        \n",
      " [9] \"Mrpl39\"        \"Jam2\"          \"Atp5j\"         \"Gabpa\"        \n",
      "[13] \"App\"           \"N6amt1\"        \"Usp16\"         \"Cct8\"         \n",
      "[17] \"Bach1\"         \"Grik1\"         \"Tiam1\"         \"Sod1\"         \n",
      "[21] \"Hunk\"          \"Urb1\"          \"Synj1\"         \"4932438H23Rik\"\n",
      "[25] \"Olig2\"         \"Olig1\"         \"Ifnar2\"        \"Il10rb\"       \n",
      "[29] \"Ifnar1\"        \"Ifngr2\"        \"Tmem50b\"       \"Dnajc28\"      \n",
      "[33] \"Gart\"          \"Son\"           \"Donson\"        \"Cryzl1\"       \n",
      "[37] \"Itsn1\"         \"Atp5o\"         \"Mrps6\"         \"Slc5a3\"       \n",
      "[41] \"Rcan1\"         \"Clic6\"         \"Setd4\"         \"Cbr1\"         \n",
      "[45] \"Cbr3\"          \"Morc3\"         \"Hlcs\"          \"Pigp\"         \n",
      "[49] \"Ttc3\"          \"Dyrk1a\"        \"Kcnj6\"         \"Ets2\"         \n",
      "[53] \"Psmg1\"         \"Brwd1\"         \"Hmgn1\"         \"Wrb\"          \n",
      "[57] \"Lca5l\"         \"B3galt5\"       \"Dscam\"         \"Prdm15\"       \n",
      "[1] \"not detected\"\n",
      "[1] 54\n",
      " [1] \"Lipi\"           \"Samsn1\"         \"mmu-miR-99a\"    \"mmu-let-7c-1\"  \n",
      " [5] \"mmu-miR-125b-2\" \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      " [9] \"Cyyr1\"          \"Adamts1\"        \"Adamts5\"        \"Zfp294\"        \n",
      "[13] \"Rwdd2b\"         \"Orf63\"          \"Cldn17\"         \"Cldn8\"         \n",
      "[17] \"Gm312\"          \"Krtap26-1\"      \"Krtap13-1\"      \"Krtap13\"       \n",
      "[21] \"Krtap16\"        \"Krtap16-7\"      \"Krtap8-1\"       \"Krtap16-4\"     \n",
      "[25] \"Krtap8-2\"       \"Sfrs15\"         \"2610039C10Rik\"  \"Mrap\"          \n",
      "[29] \"4931408A02Rik\"  \"1110004E09Rik\"  \"1810007M14Rik\"  \"Kcne2\"         \n",
      "[33] \"4930563D23Rik\"  \"Kcne1\"          \"Runx1\"          \"mmu-miR-802\"   \n",
      "[37] \"Dopey2\"         \"Chaf1b\"         \"Cldn14\"         \"Sim2\"          \n",
      "[41] \"Ripply3\"        \"Dscr3\"          \"Kcnj15\"         \"Erg\"           \n",
      "[45] \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"         \"Bace2\"         \n",
      "[49] \"Fam3b\"          \"Mx2\"            \"Tmprss2\"        \"Ripk4\"         \n",
      "[53] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Microglia\"\n",
      "[1] \"detected\"\n",
      "[1] 39\n",
      " [1] \"Samsn1\"  \"Nrip1\"   \"Usp25\"   \"Ncam2\"   \"Jam2\"    \"Atp5j\"   \"Gabpa\"  \n",
      " [8] \"App\"     \"Usp16\"   \"Cct8\"    \"Bach1\"   \"Grik1\"   \"Tiam1\"   \"Sod1\"   \n",
      "[15] \"Synj1\"   \"Ifnar2\"  \"Il10rb\"  \"Ifnar1\"  \"Ifngr2\"  \"Tmem50b\" \"Gart\"   \n",
      "[22] \"Son\"     \"Cryzl1\"  \"Itsn1\"   \"Atp5o\"   \"Mrps6\"   \"Rcan1\"   \"Runx1\"  \n",
      "[29] \"Setd4\"   \"Morc3\"   \"Hlcs\"    \"Pigp\"    \"Ttc3\"    \"Dyrk1a\"  \"Brwd1\"  \n",
      "[36] \"Hmgn1\"   \"B3galt5\" \"Dscam\"   \"Prdm15\" \n",
      "[1] \"not detected\"\n",
      "[1] 75\n",
      " [1] \"Lipi\"           \"Rbm11\"          \"Hspa13\"         \"mmu-miR-99a\"   \n",
      " [5] \"mmu-let-7c-1\"   \"mmu-miR-125b-2\" \"Cxadr\"          \"Btg3\"          \n",
      " [9] \"D16Ertd472e\"    \"Chodl\"          \"Prss7\"          \"mmu-miR-155\"   \n",
      "[13] \"Mrpl39\"         \"Cyyr1\"          \"Adamts1\"        \"Adamts5\"       \n",
      "[17] \"N6amt1\"         \"Zfp294\"         \"Rwdd2b\"         \"Orf63\"         \n",
      "[21] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[25] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[29] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[33] \"Hunk\"           \"2610039C10Rik\"  \"Mrap\"           \"Urb1\"          \n",
      "[37] \"4931408A02Rik\"  \"1110004E09Rik\"  \"1810007M14Rik\"  \"4932438H23Rik\" \n",
      "[41] \"Olig2\"          \"Olig1\"          \"Dnajc28\"        \"Donson\"        \n",
      "[45] \"Slc5a3\"         \"Kcne2\"          \"4930563D23Rik\"  \"Kcne1\"         \n",
      "[49] \"Clic6\"          \"mmu-miR-802\"    \"Cbr1\"           \"Cbr3\"          \n",
      "[53] \"Dopey2\"         \"Chaf1b\"         \"Cldn14\"         \"Sim2\"          \n",
      "[57] \"Ripply3\"        \"Dscr3\"          \"Kcnj6\"          \"Kcnj15\"        \n",
      "[61] \"Erg\"            \"Ets2\"           \"Psmg1\"          \"Wrb\"           \n",
      "[65] \"Lca5l\"          \"Sh3bgr\"         \"Igsf5\"          \"Itgb2l\"        \n",
      "[69] \"Bace2\"          \"Fam3b\"          \"Mx2\"            \"Tmprss2\"       \n",
      "[73] \"Ripk4\"          \"5830404H04Rik\"  \"Zfp295\"        \n",
      "       GABAergic Glutamatergic BFCN  OPC Oligodendrocyte Astrocyte Microglia\n",
      "Lipi          nd            nd   nd   nd              nd        nd        nd\n",
      "Rbm11         No            No <NA> <NA>              No      <NA>        nd\n",
      "Hspa13        No            No <NA> <NA>              No        No        nd\n",
      "Samsn1        No            nd   nd   nd              nd        nd        No\n",
      "Nrip1         No            No   No   No              No        No        No\n",
      "Usp25         No            No   No   No              No        No        No\n",
      "       GABAergic Glutamatergic BFCN OPC Oligodendrocyte Astrocyte Microglia\n",
      "Lipi          nd            nd   nd  nd              nd        nd        nd\n",
      "Rbm11         No            No   No  No              No        No        nd\n",
      "Hspa13        No            No   No  No              No        No        nd\n",
      "Samsn1        No            nd   nd  nd              nd        nd        No\n",
      "Nrip1         No            No   No  No              No        No        No\n",
      "Usp25         No            No   No  No              No        No        No\n",
      "[1] \"initial dims of plotMtx\"\n",
      "[1] 114   7\n",
      "[1] \"dimensions of pct exp matrix\"\n",
      "[1] 90 14\n",
      "[1] \"dim of plotMtx after subsetting for detected PctExp genes\"\n",
      "[1] 90  7\n",
      "       Astrocyte_Dp16_old Astrocyte_Dp16_yng BFCN_Dp16_old BFCN_Dp16_yng\n",
      "Rbm11           3.9556962          2.9826015     25.423729     21.653543\n",
      "Hspa13         13.9240506          9.8591549     33.050847     23.622047\n",
      "Samsn1          0.4746835          0.5799503      1.694915      1.574803\n",
      "Nrip1          32.5949367         23.9436620     68.644068     68.503937\n",
      "Usp25          34.9683544         23.3637117     62.711864     52.755906\n",
      "Cxadr          17.0886076         11.5161558     47.457627     43.700787\n",
      "       GABAergic_Dp16_old GABAergic_Dp16_yng Glutamatergic_Dp16_old\n",
      "Rbm11           9.1720503          6.3872472              9.3628809\n",
      "Hspa13         17.8850731         14.8240525             21.1634349\n",
      "Samsn1          0.5015301          0.3470151              0.7202216\n",
      "Nrip1          31.8259096         25.1640189             34.5152355\n",
      "Usp25          43.5056103         31.3126932             45.9279778\n",
      "Cxadr          40.8364502         27.4413056             45.9833795\n",
      "       Glutamatergic_Dp16_yng Microglia_Dp16_old Microglia_Dp16_yng\n",
      "Rbm11               6.9778189          0.1277139          0.0000000\n",
      "Hspa13             17.3290203          1.7879949          1.5901060\n",
      "Samsn1              0.5545287         15.7088123         10.0706714\n",
      "Nrip1              24.4916821         49.2975734         40.7243816\n",
      "Usp25              35.4436229         18.9016603          9.9823322\n",
      "Cxadr              28.8817006          0.6385696          0.5300353\n",
      "       Oligodendrocyte_Dp16_old Oligodendrocyte_Dp16_yng OPC_Dp16_old\n",
      "Rbm11                1.56583630                1.2663399   12.1126761\n",
      "Hspa13               2.84697509                1.4705882   16.3380282\n",
      "Samsn1               0.07117438                0.0000000    0.2816901\n",
      "Nrip1               12.74021352               11.9689542   28.1690141\n",
      "Usp25               21.42348754               16.3398693   39.7183099\n",
      "Cxadr                0.88967972                0.2042484   27.3239437\n",
      "       OPC_Dp16_yng\n",
      "Rbm11     8.0617496\n",
      "Hspa13   15.9519726\n",
      "Samsn1    0.3430532\n",
      "Nrip1    27.4442539\n",
      "Usp25    29.3310463\n",
      "Cxadr    23.1560892\n",
      "[1] \"keep genes\"\n",
      " [1] \"4932438H23Rik\" \"Adamts1\"       \"Adamts5\"       \"App\"          \n",
      " [5] \"Atp5j\"         \"Atp5o\"         \"B3galt5\"       \"Bace2\"        \n",
      " [9] \"Bach1\"         \"Brwd1\"         \"Btg3\"          \"Cbr1\"         \n",
      "[13] \"Cbr3\"          \"Cct8\"          \"Chodl\"         \"Cldn14\"       \n",
      "[17] \"Clic6\"         \"Cryzl1\"        \"Cxadr\"         \"Cyyr1\"        \n",
      "[21] \"D16Ertd472e\"   \"Dnajc28\"       \"Donson\"        \"Dscam\"        \n",
      "[25] \"Dyrk1a\"        \"Ets2\"          \"Gabpa\"         \"Gart\"         \n",
      "[29] \"Grik1\"         \"Hlcs\"          \"Hmgn1\"         \"Hspa13\"       \n",
      "[33] \"Hunk\"          \"Ifnar1\"        \"Ifnar2\"        \"Ifngr2\"       \n",
      "[37] \"Igsf5\"         \"Il10rb\"        \"Itsn1\"         \"Jam2\"         \n",
      "[41] \"Kcnj6\"         \"Lca5l\"         \"Morc3\"         \"Mrpl39\"       \n",
      "[45] \"Mrps6\"         \"N6amt1\"        \"Ncam2\"         \"Nrip1\"        \n",
      "[49] \"Olig1\"         \"Olig2\"         \"Pigp\"          \"Prdm15\"       \n",
      "[53] \"Psmg1\"         \"Rbm11\"         \"Rcan1\"         \"Ripk4\"        \n",
      "[57] \"Runx1\"         \"Rwdd2b\"        \"Samsn1\"        \"Setd4\"        \n",
      "[61] \"Sh3bgr\"        \"Slc5a3\"        \"Sod1\"          \"Son\"          \n",
      "[65] \"Synj1\"         \"Tiam1\"         \"Tmem50b\"       \"Ttc3\"         \n",
      "[69] \"Urb1\"          \"Usp16\"         \"Usp25\"         \"Wrb\"          \n",
      "[1] 72\n",
      "[1] \"subset plotMtx for passing pctExp genes\"\n",
      "[1] 72  7\n",
      "[1] 72  7\n",
      "       Astrocyte  Microglia Oligodendrocyte        OPC        BFCN  GABAergic\n",
      "Rbm11  0.2567720 0.00000000     -0.21774837  0.3190440 -0.14558634  0.2086911\n",
      "Hspa13 0.2658920 0.00000000      0.43405623 -0.4122215  0.18752851 -0.1536817\n",
      "Samsn1 0.0000000 0.47601835      0.00000000  0.0000000  0.00000000  0.5559112\n",
      "Nrip1  0.2372267 0.05470513     -0.37678185 -0.1201510 -0.23326744  0.1662311\n",
      "Usp25  0.5277448 0.51228537     -0.02298244  0.4153594  0.15314983  0.3303855\n",
      "Cxadr  0.3907145 0.00000000      1.84844040  0.2274803  0.04874068  0.4070433\n",
      "       Glutamatergic\n",
      "Rbm11     0.03074049\n",
      "Hspa13   -0.09130245\n",
      "Samsn1    0.00000000\n",
      "Nrip1     0.23725786\n",
      "Usp25     0.20754696\n",
      "Cxadr     0.45291148\n",
      "[1] 72  7\n",
      "       Astrocyte Microglia Oligodendrocyte OPC BFCN GABAergic Glutamatergic\n",
      "Rbm11         No        nd              --  No   No        No            No\n",
      "Hspa13        No        nd              No  No   No        No            No\n",
      "Samsn1        nd        No              nd  nd   nd        --            nd\n",
      "Nrip1         No        No              No  No   No        No            No\n",
      "Usp25         No        No              No  No   No        No            No\n",
      "Cxadr         No        nd              --  No   No        No            No\n",
      "[1] \"DONE: Dp16_old-Dp16_yng\"\n"
     ]
    }
   ],
   "source": [
    "### NOW LOOP THROUGH AND MAKE HMAPS FOR EACH PAIRWISE COMPARISON ###\n",
    "### AKA ONE PLOT PER COMPARISON; X-AXIS = CELLTYPES ###\n",
    "DefaultAssay(sobj_nodoub) <- \"RNA\"\n",
    "Idents(sobj_nodoub) <- \"conditions\"\n",
    "\n",
    "PCTEXPTHRES <- 2.5\n",
    "celltypes <- unique(sobj$broad_celltypes)\n",
    "celltypes <- celltypes[!celltypes == \"Doublet\"] \n",
    "#pairs <- c(\"2N_old-2N_yng\", \"Dp16_old-2N_old\", \"Dp16_old-2N_yng\", \"Dp16_old-Dp16_yng\", \"Dp16_yng-2N_old\", \"Dp16_yng-2N_yng\")\n",
    "\n",
    "pairs <- c(\"Dp16_yng-2N_yng\",\"Dp16_old-2N_old\",\"Dp16_old-Dp16_yng\")\n",
    "\n",
    "#pairs <- c(\"Dp16_old-2N_old\")\n",
    "for(p in pairs){\n",
    "    PAIR_ODIR <- paste0(NA_ODIR, p, \"/\")\n",
    "    suppressWarnings(dir.create(PAIR_ODIR))\n",
    "    \n",
    "    print(paste0(\"STARTING: \", p))\n",
    "\n",
    "    # grab all pairwise specific deseq files\n",
    "    deseq_files <- list.files(DE_PATH, p, full.names = T)\n",
    "\n",
    "    # signif \"*\" dataframe for hmap\n",
    "    signif_df <- data.frame(matrix(\"No\", ncol = length(celltypes), nrow = length(tri16Genes))) # contains - log2fc, padj, celltype, and signif cols\n",
    "    rownames(signif_df) <- tri16Genes\n",
    "    colnames(signif_df) <- celltypes\n",
    "        \n",
    "    # try to make this tri16genes x celltype dims\n",
    "    plotMtx <- as.data.frame(matrix(0, ncol = length(celltypes), nrow = length(tri16Genes))) # contains - just log2fc for each celltype\n",
    "    rownames(plotMtx) <- tri16Genes\n",
    "    colnames(plotMtx) <- celltypes\n",
    "\n",
    "    pdata <- data.frame() # contains - log2fc, padj, celltype, and signif cols\n",
    "    for(ct in celltypes){\n",
    "        print(ct)\n",
    "    \n",
    "        # grab the celltype specific deseq file and subset for tri16 genelist\n",
    "        ct_deseq <- read.csv(grep(ct, deseq_files, value = T), row.names = 1)[,c(\"log2FoldChange\",\"padj\")]\n",
    "        ct_deseq_tri16 <- ct_deseq[which(rownames(ct_deseq) %in% tri16Genes),]\n",
    "        print(\"detected\")\n",
    "        print(nrow(ct_deseq_tri16))\n",
    "        ct_deseq_tri16$Celltype <- ct\n",
    "        ct_deseq_tri16$Gene <- rownames(ct_deseq_tri16)\n",
    "        print(ct_deseq_tri16$Gene)\n",
    "        \n",
    "        ct_deseq_tri16$Signif <- ifelse(ct_deseq_tri16$padj <= 0.05, \"Yes\", \"No\")\n",
    "        #print(dim(ct_deseq_tri16))\n",
    "    \n",
    "        pdata <- rbind(pdata, ct_deseq_tri16)\n",
    "        signif_df[rownames(ct_deseq_tri16),ct] <- ifelse(ct_deseq_tri16$padj <= 0.05, \"Yes\", \"No\")\n",
    "        \n",
    "        # just adding log2fc to dataframe without padj and other cols - maybe this will work better?\n",
    "        plotMtx[rownames(ct_deseq_tri16),ct] <- ct_deseq_tri16$log2FoldChange\n",
    "\n",
    "        # go through genes that are NOT detected in tri16Genes and in the signif df label as 'nd'\n",
    "        nd_tri16 <- setdiff(tri16Genes, ct_deseq_tri16$Gene)\n",
    "        print(\"not detected\")\n",
    "        print(length(nd_tri16))\n",
    "        print(nd_tri16)\n",
    "        signif_df[nd_tri16,ct] <- \"nd\"\n",
    "    }\n",
    "\n",
    "    print(head(signif_df))\n",
    "    ### 240927 KD edit - adding back in NA's from DESeq2 ex: Il10rb has padj = NA ###\n",
    "    ### write these down as \"No\" in significance ###\n",
    "    signif_df[is.na(signif_df)] <- \"No\"\n",
    "    print(head(signif_df))\n",
    "\n",
    "    print(\"initial dims of plotMtx\")\n",
    "    print(dim(plotMtx))\n",
    "\n",
    "    # print the pdata (df with signif col - can be used to \"*\" indicate DEG)\n",
    "    write.csv(pdata, paste0(PAIR_ODIR, p, \"_Tri16_DEGsummary.csv\"))\n",
    "\n",
    "    ### done making plot data (plotMtx) - now on the plotting section ###  \n",
    "    # in order for a gene to pass the pct exp thres,\n",
    "    # it must be in at least one condition of the pair of one celltype\n",
    "    cond1 <- str_split(p, pattern = \"-\")[[1]][1]\n",
    "    cond2 <- str_split(p, pattern = \"-\")[[1]][2]\n",
    "    sobj_nodoub_cond <- subset(sobj_nodoub, idents = c(cond1, cond2))\n",
    "    \n",
    "    pctExp <- suppressWarnings(Percent_Expressing(sobj_nodoub_cond, features = tri16Genes,\n",
    "                                                  group_by = \"broad_celltypes\", split_by = \"conditions\")) # 90ish genes\n",
    "    pctExp <- pctExp[,sort(colnames(pctExp))]\n",
    "    write.csv(pctExp, paste0(PAIR_ODIR, p, \"_NO_pctExpKeptGenes.csv\"))\n",
    "    \n",
    "    print(\"dimensions of pct exp matrix\")\n",
    "    print(dim(pctExp))\n",
    "    # subset plotMtx for the genes that were detected in the Percent_Expressing function\n",
    "    plotMtx <- plotMtx[(rownames(plotMtx) %in% rownames(pctExp)),]\n",
    "\n",
    "    print(\"dim of plotMtx after subsetting for detected PctExp genes\")\n",
    "    print(dim(plotMtx))\n",
    "    \n",
    "    pctExp <- pctExp[apply(pctExp, 1, max) >= PCTEXPTHRES, ]\n",
    "    write.csv(pctExp, paste0(PAIR_ODIR, p, \"_\", PCTEXPTHRES, \"_pctExpKeptGenes.csv\"))\n",
    "    \n",
    "    print(head(pctExp))\n",
    "    keepgenes <- rownames(pctExp)\n",
    "    print(\"keep genes\")\n",
    "    print(sort(keepgenes))\n",
    "    print(length(keepgenes))\n",
    "\n",
    "    print(\"subset plotMtx for passing pctExp genes\")\n",
    "    plotMtx_pctexp <- plotMtx[which(rownames(plotMtx) %in% keepgenes),]\n",
    "    print(dim(plotMtx_pctexp))\n",
    "    \n",
    "    # rearrange the celltype order\n",
    "    plotMtx_pctexp <- plotMtx_pctexp[,c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN',\"GABAergic\",\"Glutamatergic\")]\n",
    "    #plotMtx <- plotMtx[,c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN',\"GABAergic\",\"Glutamatergic\")]\n",
    "    \n",
    "    # subset signif signif_df df to match plotMtx exactly\n",
    "    signif_df <- signif_df[which(rownames(signif_df) %in% rownames(plotMtx_pctexp)), c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN',\"GABAergic\",\"Glutamatergic\")]\n",
    "    #signif_df <- signif_df[which(rownames(signif_df) %in% rownames(plotMtx)), c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN',\"GABAergic\",\"Glutamatergic\")]\n",
    "\n",
    "    ### go through pctExp and for the genes that pass the pct exp cutoff, add \"nd\" on the values that didn't pass the N% ###\n",
    "    # ex: pct exp in Astrocytes Dp16_old = 5% and Dp16_yng = 7% for geneA = \"nd\"\n",
    "    # ex: pct exp in Astrocytes Dp16_old = 11% and Dp16_yng = 7% for geneA = detected\n",
    "    # going through all of the genes passed the pct exp threshold\n",
    "    # and need to add \"nd\" if lowly detected in that specific celltype\n",
    "    # ex: 5% in cond1 vs 15% in cond2 in ONE celltype = detected\n",
    "    # ex: 5% in cond1 vs 2% in cond2 in ONE celltype = nd\n",
    "    for(gene in keepgenes){\n",
    "        for(ct in celltypes){\n",
    "            cond1_pctExp <- pctExp[gene,grep(ct, colnames(pctExp), value = TRUE)][1,1]\n",
    "            cond2_pctExp <- pctExp[gene,grep(ct, colnames(pctExp), value = TRUE)][1,2]\n",
    "            if((max(cond1_pctExp, cond2_pctExp) <= PCTEXPTHRES) & !(signif_df[gene,ct] %in% c(\"Yes\", \"nd\"))){\n",
    "                signif_df[gene,ct] <- \"--\"\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    ### done adding \"nd\"\n",
    "    \n",
    "    # function to make heatmaps (log2FC, log10FC, z-score log2FC)\n",
    "    print(dim(plotMtx_pctexp))\n",
    "    print(head(plotMtx_pctexp))\n",
    "    #print(dim(plotMtx))\n",
    "    print(dim(signif_df))\n",
    "    print(head(signif_df))\n",
    "    \n",
    "    #hmap_list <- plotHmaps(plotMtx_pctexp, PAIR_ODIR, signif_df, p, PCTEXPTHRES)\n",
    "    print(paste0(\"DONE: \", p))\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e472938-41f7-4f0a-8413-8ef493807f28",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "659fd72d-3592-445e-baeb-6ddee8061b8b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53408571-ab22-45b6-9bac-5bf8f5f40f47",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8179f2a7-6624-474e-bc6c-c7579f0573e6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac145eea-318f-4e64-893b-8565a79f4d38",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "afca6b19-e077-4922-b707-e4cfd8a33c41",
   "metadata": {},
   "source": [
    "### flip around hmaps: x-axis = comparisons; 7 broad celltypes * 3 plots (different way to plot logfc) = 21 pdfs\n",
    "point of previous hmaps (x = celltypes): looking at which celltype is the most \"affected\" (has the most significant FC) by a condition; comparing celltypes to each other based on the FC of Tri16 genes  \n",
    "point of these new hmaps (x = pairs): looking at which comparison/condition (\"/condition\" because based on the direction i can see if say Dp16_old is the driving condition in differential expression) has the most significant FC for an individual celltype; comparing pairwise comparisons against each other\n",
    "\n",
    "### X-AXIS = COMPARISONS\n",
    "FOR THE PCT EXP NEED TO COMPARE FOR JUST THAT CELLTYPE DONT NEED TO PAY ATTENTION TO THE OTHER CELLTYPES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "433d6f4c-6f95-4531-942d-b5f00abb3b70",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"STARTING: GABAergic\"\n",
      "[1] \"2N_old-2N_yng\"\n",
      "[1] \"detected\"\n",
      "[1] 75\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Dscam\"         \"Bace2\"        \n",
      "[73] \"Fam3b\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] 75  5\n",
      "[1] \"not detected\"\n",
      "[1] 39\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Igsf5\"          \"Itgb2l\"         \"Mx2\"           \n",
      "[37] \"Tmprss2\"        \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Dp16_old-2N_old\"\n",
      "[1] \"detected\"\n",
      "[1] 75\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] 75  5\n",
      "[1] \"not detected\"\n",
      "[1] 39\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Fam3b\"          \"Mx2\"           \n",
      "[37] \"Tmprss2\"        \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Dp16_old-2N_yng\"\n",
      "[1] \"detected\"\n",
      "[1] 76\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Fam3b\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] 76  5\n",
      "[1] \"not detected\"\n",
      "[1] 38\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Mx2\"            \"Tmprss2\"       \n",
      "[37] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Dp16_old-Dp16_yng\"\n",
      "[1] \"detected\"\n",
      "[1] 76\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Fam3b\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] 76  5\n",
      "[1] \"not detected\"\n",
      "[1] 38\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Mx2\"            \"Tmprss2\"       \n",
      "[37] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Dp16_yng-2N_old\"\n",
      "[1] \"detected\"\n",
      "[1] 76\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Fam3b\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] 76  5\n",
      "[1] \"not detected\"\n",
      "[1] 38\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Mx2\"            \"Tmprss2\"       \n",
      "[37] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "[1] \"Dp16_yng-2N_yng\"\n",
      "[1] \"detected\"\n",
      "[1] 76\n",
      " [1] \"Rbm11\"         \"Hspa13\"        \"Samsn1\"        \"Nrip1\"        \n",
      " [5] \"Usp25\"         \"Cxadr\"         \"Btg3\"          \"D16Ertd472e\"  \n",
      " [9] \"Chodl\"         \"Ncam2\"         \"Mrpl39\"        \"Jam2\"         \n",
      "[13] \"Atp5j\"         \"Gabpa\"         \"App\"           \"Cyyr1\"        \n",
      "[17] \"Adamts1\"       \"Adamts5\"       \"N6amt1\"        \"Rwdd2b\"       \n",
      "[21] \"Usp16\"         \"Cct8\"          \"Bach1\"         \"Grik1\"        \n",
      "[25] \"Tiam1\"         \"Sod1\"          \"Hunk\"          \"Urb1\"         \n",
      "[29] \"Synj1\"         \"4932438H23Rik\" \"Olig2\"         \"Olig1\"        \n",
      "[33] \"Ifnar2\"        \"Il10rb\"        \"Ifnar1\"        \"Ifngr2\"       \n",
      "[37] \"Tmem50b\"       \"Dnajc28\"       \"Gart\"          \"Son\"          \n",
      "[41] \"Donson\"        \"Cryzl1\"        \"Itsn1\"         \"Atp5o\"        \n",
      "[45] \"Mrps6\"         \"Slc5a3\"        \"Kcne2\"         \"Rcan1\"        \n",
      "[49] \"Clic6\"         \"Runx1\"         \"Setd4\"         \"Cbr1\"         \n",
      "[53] \"Cbr3\"          \"Morc3\"         \"Cldn14\"        \"Sim2\"         \n",
      "[57] \"Hlcs\"          \"Pigp\"          \"Ttc3\"          \"Dyrk1a\"       \n",
      "[61] \"Kcnj6\"         \"Erg\"           \"Ets2\"          \"Psmg1\"        \n",
      "[65] \"Brwd1\"         \"Hmgn1\"         \"Wrb\"           \"Lca5l\"        \n",
      "[69] \"Sh3bgr\"        \"B3galt5\"       \"Igsf5\"         \"Dscam\"        \n",
      "[73] \"Bace2\"         \"Fam3b\"         \"Ripk4\"         \"Prdm15\"       \n",
      "[1] 76  5\n",
      "[1] \"not detected\"\n",
      "[1] 38\n",
      " [1] \"Lipi\"           \"mmu-miR-99a\"    \"mmu-let-7c-1\"   \"mmu-miR-125b-2\"\n",
      " [5] \"Prss7\"          \"mmu-miR-155\"    \"Zfp294\"         \"Orf63\"         \n",
      " [9] \"Cldn17\"         \"Cldn8\"          \"Gm312\"          \"Krtap26-1\"     \n",
      "[13] \"Krtap13-1\"      \"Krtap13\"        \"Krtap16\"        \"Krtap16-7\"     \n",
      "[17] \"Krtap8-1\"       \"Krtap16-4\"      \"Krtap8-2\"       \"Sfrs15\"        \n",
      "[21] \"2610039C10Rik\"  \"Mrap\"           \"4931408A02Rik\"  \"1110004E09Rik\" \n",
      "[25] \"1810007M14Rik\"  \"4930563D23Rik\"  \"Kcne1\"          \"mmu-miR-802\"   \n",
      "[29] \"Dopey2\"         \"Chaf1b\"         \"Ripply3\"        \"Dscr3\"         \n",
      "[33] \"Kcnj15\"         \"Itgb2l\"         \"Mx2\"            \"Tmprss2\"       \n",
      "[37] \"5830404H04Rik\"  \"Zfp295\"        \n",
      "       2N_old-2N_yng Dp16_old-2N_old Dp16_old-2N_yng Dp16_old-Dp16_yng\n",
      "Lipi              nd              nd              nd                nd\n",
      "Rbm11             No             Yes             Yes                No\n",
      "Hspa13            No              No              No                No\n",
      "Samsn1            No            <NA>              No                No\n",
      "Nrip1             No             Yes             Yes                No\n",
      "Usp25             No             Yes             Yes                No\n",
      "       Dp16_yng-2N_old Dp16_yng-2N_yng\n",
      "Lipi                nd              nd\n",
      "Rbm11               No              No\n",
      "Hspa13              No              No\n",
      "Samsn1              No            <NA>\n",
      "Nrip1               No              No\n",
      "Usp25               No              No\n",
      "       2N_old-2N_yng Dp16_old-2N_old Dp16_old-2N_yng Dp16_old-Dp16_yng\n",
      "Lipi              nd              nd              nd                nd\n",
      "Rbm11             No             Yes             Yes                No\n",
      "Hspa13            No              No              No                No\n",
      "Samsn1            No              No              No                No\n",
      "Nrip1             No             Yes             Yes                No\n",
      "Usp25             No             Yes             Yes                No\n",
      "       Dp16_yng-2N_old Dp16_yng-2N_yng\n",
      "Lipi                nd              nd\n",
      "Rbm11               No              No\n",
      "Hspa13              No              No\n",
      "Samsn1              No              No\n",
      "Nrip1               No              No\n",
      "Usp25               No              No\n",
      "[1] 114   6\n",
      "[1] 76  6\n",
      "[1] \"dimensions of pct exp matrix\"\n",
      "[1] 90  4\n",
      "[1] \"dim of plotMtx after subsetting for detected PctExp genes\"\n",
      "[1] 76  6\n",
      "       Dp16_old   X2N_old  Dp16_yng   X2N_yng\n",
      "Rbm11   9.17205  3.290704  6.387247  4.341711\n",
      "Hspa13 17.88507 10.328322 14.824052 11.954993\n",
      "Nrip1  31.82591 15.810336 25.164019 20.956399\n",
      "Usp25  43.50561 19.901279 31.312693 25.542714\n",
      "Cxadr  40.83645 17.096702 27.441306 22.742005\n",
      "Btg3   16.78001  6.835689 13.745052  9.790253\n",
      "       Dp16_old    2N_old  Dp16_yng    2N_yng\n",
      "Rbm11   9.17205  3.290704  6.387247  4.341711\n",
      "Hspa13 17.88507 10.328322 14.824052 11.954993\n",
      "Nrip1  31.82591 15.810336 25.164019 20.956399\n",
      "Usp25  43.50561 19.901279 31.312693 25.542714\n",
      "Cxadr  40.83645 17.096702 27.441306 22.742005\n",
      "Btg3   16.78001  6.835689 13.745052  9.790253\n",
      "[1] \"keep genes in plotMtx_pctexp\"\n",
      " [1] \"4932438H23Rik\" \"App\"           \"Atp5j\"         \"Atp5o\"        \n",
      " [5] \"B3galt5\"       \"Bach1\"         \"Brwd1\"         \"Btg3\"         \n",
      " [9] \"Cbr1\"          \"Cbr3\"          \"Cct8\"          \"Chodl\"        \n",
      "[13] \"Clic6\"         \"Cryzl1\"        \"Cxadr\"         \"D16Ertd472e\"  \n",
      "[17] \"Dnajc28\"       \"Donson\"        \"Dscam\"         \"Dyrk1a\"       \n",
      "[21] \"Ets2\"          \"Gabpa\"         \"Gart\"          \"Grik1\"        \n",
      "[25] \"Hlcs\"          \"Hmgn1\"         \"Hspa13\"        \"Hunk\"         \n",
      "[29] \"Ifnar1\"        \"Ifnar2\"        \"Ifngr2\"        \"Itsn1\"        \n",
      "[33] \"Jam2\"          \"Kcnj6\"         \"Lca5l\"         \"Morc3\"        \n",
      "[37] \"Mrpl39\"        \"Mrps6\"         \"N6amt1\"        \"Ncam2\"        \n",
      "[41] \"Nrip1\"         \"Olig1\"         \"Pigp\"          \"Prdm15\"       \n",
      "[45] \"Psmg1\"         \"Rbm11\"         \"Rcan1\"         \"Setd4\"        \n",
      "[49] \"Slc5a3\"        \"Sod1\"          \"Son\"           \"Synj1\"        \n",
      "[53] \"Tiam1\"         \"Tmem50b\"       \"Ttc3\"          \"Urb1\"         \n",
      "[57] \"Usp16\"         \"Usp25\"         \"Wrb\"          \n",
      "[1] 59\n",
      "[1] 59  6\n",
      "[1] \"stopping here\"\n"
     ]
    }
   ],
   "source": [
    "### NOW LOOP THROUGH AND MAKE HMAPS FOR EACH PAIRWISE COMPARISON ###\n",
    "### AKA ONE PLOT PER CELLTYPE; X-AXIS = COMPARISONS ###\n",
    "DefaultAssay(sobj) <- \"RNA\"\n",
    "PCTEXPTHRES <- 2.5\n",
    "pairs <- c(\"2N_old-2N_yng\", \"Dp16_old-2N_old\", \"Dp16_old-2N_yng\", \"Dp16_old-Dp16_yng\", \"Dp16_yng-2N_old\", \"Dp16_yng-2N_yng\")\n",
    "#for(p in pairs){\n",
    "celltypes <- unique(sobj$broad_celltypes)\n",
    "celltypes <- celltypes[!celltypes == \"Doublet\"] # rem doublets\n",
    "celltypes <- \"GABAergic\" # KD edit - only wanted y-scale for GABAergic neurons\n",
    "for(ct in celltypes){\n",
    "    PAIR_ODIR <- paste0(NA_ODIR, ct, \"/\")\n",
    "    suppressWarnings(dir.create(PAIR_ODIR))\n",
    "    \n",
    "    print(paste0(\"STARTING: \", ct))\n",
    "\n",
    "    # grab all pairwise specific deseq files\n",
    "    deseq_files <- list.files(DE_PATH, ct, full.names = T)\n",
    "\n",
    "    # signif \"*\" dataframe for hmap\n",
    "    signif_df <- data.frame(matrix(\"No\", ncol = length(pairs), nrow = length(tri16Genes))) # contains - log2fc, padj, celltype, and signif cols\n",
    "    rownames(signif_df) <- tri16Genes\n",
    "    colnames(signif_df) <- pairs\n",
    "        \n",
    "    # try to make this tri16genes x celltype dims\n",
    "    plotMtx <- as.data.frame(matrix(0, ncol = length(pairs), nrow = length(tri16Genes))) # contains - just log2fc for each celltype\n",
    "    rownames(plotMtx) <- tri16Genes\n",
    "    colnames(plotMtx) <- pairs\n",
    "\n",
    "    #celltypes <- unique(sobj$broad_celltypes)\n",
    "    #celltypes <- celltypes[!celltypes == \"Doublet\"] # rem doublets\n",
    "    pdata <- data.frame() # contains - log2fc, padj, celltype, and signif cols\n",
    "    #pairs <- c(\"2N_old-2N_yng\", \"Dp16_old-2N_old\", \"Dp16_old-2N_yng\", \"Dp16_old-Dp16_yng\", \"Dp16_yng-2N_old\", \"Dp16_yng-2N_yng\")\n",
    "    for(p in pairs){\n",
    "    #for(ct in celltypes){\n",
    "        print(p)\n",
    "    \n",
    "        # grab the celltype specific deseq file and subset for tri16 genelist\n",
    "        ct_deseq <- read.csv(grep(p, deseq_files, value = T), row.names = 1)[,c(\"log2FoldChange\",\"padj\")]\n",
    "        ct_deseq_tri16 <- ct_deseq[which(rownames(ct_deseq) %in% tri16Genes),]\n",
    "        ct_deseq_tri16$Celltype <- p\n",
    "        ct_deseq_tri16$Gene <- rownames(ct_deseq_tri16)\n",
    "        print(\"detected\")\n",
    "        print(nrow(ct_deseq_tri16))\n",
    "        print(ct_deseq_tri16$Gene)\n",
    "        \n",
    "        ct_deseq_tri16$Signif <- ifelse(ct_deseq_tri16$padj <= 0.05, \"Yes\", \"No\")\n",
    "        print(dim(ct_deseq_tri16))\n",
    "    \n",
    "        pdata <- rbind(pdata, ct_deseq_tri16)\n",
    "        signif_df[rownames(ct_deseq_tri16),p] <- ifelse(ct_deseq_tri16$padj <= 0.05, \"Yes\", \"No\")\n",
    "    \n",
    "        # just adding log2fc to dataframe without padj and other cols - maybe this will work better?\n",
    "        plotMtx[rownames(ct_deseq_tri16),p] <- ct_deseq_tri16$log2FoldChange\n",
    "\n",
    "        # go through genes that are NOT detected in tri16Genes and in the signif df label as 'nd'\n",
    "        nd_tri16 <- setdiff(tri16Genes, ct_deseq_tri16$Gene)\n",
    "        print(\"not detected\")\n",
    "        print(length(nd_tri16))\n",
    "        print(nd_tri16)\n",
    "\n",
    "        signif_df[nd_tri16,p] <- \"nd\"\n",
    "    }\n",
    "\n",
    "    print(head(signif_df))\n",
    "    ### 240927 KD edit - adding back in NA's from DESeq2 ex: Il10rb has padj = NA ###\n",
    "    ### write these down as \"No\" in significance ###\n",
    "    signif_df[is.na(signif_df)] <- \"No\"\n",
    "    print(head(signif_df))\n",
    "    \n",
    "    # print the pdata (df with signif col - can be used to \"*\" indicate DEG)\n",
    "    write.csv(pdata, paste0(PAIR_ODIR, ct, \"_Tri16_DEGsummary.csv\"))\n",
    "\n",
    "    ### done making plot data (plotMtx) - now on the plotting section ###    \n",
    "    # maybe remove genes that have zeros across all celltypes\n",
    "    print(dim(plotMtx))\n",
    "    plotMtx <- plotMtx[rowSums(plotMtx) != 0, ]\n",
    "    print(dim(plotMtx))\n",
    "    \n",
    "    # applying N% min exp cutoff\n",
    "    # the gene must be exp in at least N% of one of the conditions in that specific celltype\n",
    "    ct_sobj <- subset(sobj, subset = broad_celltypes == ct)\n",
    "    pctExp <- suppressWarnings(Percent_Expressing(ct_sobj, features = tri16Genes, group_by = \"conditions\"))\n",
    "    write.csv(pctExp, paste0(PAIR_ODIR, ct, \"_NO_pctExpKeptGenes.csv\"))\n",
    "\n",
    "    print(\"dimensions of pct exp matrix\")\n",
    "    print(dim(pctExp))\n",
    "    # subset plotMtx for the genes that were detected in the Percent_Expressing function\n",
    "    plotMtx <- plotMtx[(rownames(plotMtx) %in% rownames(pctExp)),]\n",
    "\n",
    "    print(\"dim of plotMtx after subsetting for detected PctExp genes\")\n",
    "    print(dim(plotMtx))\n",
    "    \n",
    "    pctExp <- pctExp[apply(pctExp, 1, max) >= PCTEXPTHRES, ]\n",
    "    print(head(pctExp))\n",
    "    colnames(pctExp) <- c(\"Dp16_old\",\"2N_old\",\"Dp16_yng\",\"2N_yng\")\n",
    "    print(head(pctExp))\n",
    "    write.csv(pctExp, paste0(PAIR_ODIR, ct, \"_\", PCTEXPTHRES, \"_pctExpKeptGenes.csv\"))\n",
    "    \n",
    "    keepgenes <- rownames(pctExp)\n",
    "    #keepgenes <- rownames(pctExp[pctExp[[ct]] >= 10,])\n",
    "    print(\"keep genes in plotMtx_pctexp\")\n",
    "    print(sort(keepgenes))\n",
    "    print(length(keepgenes))\n",
    "\n",
    "    ### 240927 - problem with doing this is that it removes genes where it is lowly exp. in each comparison\n",
    "    ### ex: Il10rb\t1.428085685\t0.598309775\t1.18744239\t0.672659451 --> vals = pct.exp\n",
    "    ### these are all lowly expressed (< 2.5%) so instead of having \"--\" across the entire line, i just removed it\n",
    "    ### check if this is what we want... i think we should remove genes that are lowly expressed across all pairwise comparisons\n",
    "    plotMtx_pctexp <- plotMtx[which(rownames(plotMtx) %in% keepgenes),]\n",
    "\n",
    "    # rearrange the celltype order\n",
    "    #plotMtx_pctexp <- plotMtx_pctexp[,c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN',\"GABAergic\",\"Glutamatergic\")]\n",
    "    \n",
    "    # subset signif signif_df df to match plotMtx exactly\n",
    "    signif_df <- signif_df[which(rownames(signif_df) %in% rownames(plotMtx_pctexp)),]\n",
    "    print(dim(signif_df))\n",
    "    print(\"stopping here\")\n",
    "    break\n",
    "\n",
    "    ### go through pctExp and for the genes that pass the pct exp cutoff, add \"--\" on the values that didn't pass the N% ###\n",
    "    # ex: (thres = 10%) in Astrocytes, pct exp: 2N_old = 5%, 2N_yng = 7%, Dp16_yng = 1%, Dp16_old = 8%. for geneA = \"--\"/low detection\n",
    "    # ex: (thres = 10%) in Astrocytes, pct exp: 2N_old = 15%, 2N_yng = 7%, Dp16_yng = 11%, Dp16_old = 8%. for geneA = passed thres\n",
    "    # need to add \"--\" if lowly detected in that conditions for that celltype\n",
    "    for(gene in keepgenes){\n",
    "        for(p in pairs){\n",
    "            cond1 <- str_split(p, pattern = \"-\")[[1]][1]\n",
    "            cond2 <- str_split(p, pattern = \"-\")[[1]][2]\n",
    "            cond1_pctExp <- pctExp[gene,grep(cond1, colnames(pctExp), value = TRUE)]\n",
    "            cond2_pctExp <- pctExp[gene,grep(cond2, colnames(pctExp), value = TRUE)]\n",
    "            if((max(cond1_pctExp, cond2_pctExp) <= PCTEXPTHRES) & !(signif_df[gene,p] %in% c(\"Yes\", \"nd\"))){\n",
    "                signif_df[gene,p] <- \"--\"\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    ### done adding \"low detected\"/\"--\" genes\n",
    "    \n",
    "    # function to make heatmaps (log2FC, log10FC, z-score log2FC)\n",
    "    print(head(plotMtx_pctexp))\n",
    "    print(head(signif_df))\n",
    "    #hmap_list <- plotHmaps(plotMtx_pctexp, PAIR_ODIR, signif_df, ct, PCTEXPTHRES)\n",
    "    print(paste0(\"DONE: \", ct))\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7da27aa3-8612-4a75-83b6-e13128b49f99",
   "metadata": {},
   "source": [
    "# Done with heatmaps (x-axis = celltypes and pairwise comparisons)\n",
    "### now make the dotplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b76758f3-0d6f-412e-8296-f2270fab5e07",
   "metadata": {},
   "outputs": [],
   "source": [
    "source(\"/tscc/projects/ps-epigen/users/kdang/scripts/source_FunFig.R\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9e7f9ecc-bd9c-40b1-af58-107464cf35ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "IDIR <- \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fce7168a-78dd-4a10-81bc-00d62783c960",
   "metadata": {},
   "source": [
    "### dotplot for hmaps with x-axis = pairwise comparisons\n",
    "AKA where the directories are the celltypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c03f1920-1989-4d6f-85cd-d08ab2259dcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>GABAergic</li><li>Glutamatergic</li><li>BFCN</li><li>OPC</li><li>Oligodendrocyte</li><li>Astrocyte</li><li>Microglia</li></ol>\n",
       "\n",
       "<details>\n",
       "\t<summary style=display:list-item;cursor:pointer>\n",
       "\t\t<strong>Levels</strong>:\n",
       "\t</summary>\n",
       "\t<style>\n",
       "\t.list-inline {list-style: none; margin:0; padding: 0}\n",
       "\t.list-inline>li {display: inline-block}\n",
       "\t.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "\t</style>\n",
       "\t<ol class=list-inline><li>'Astrocyte'</li><li>'Microglia'</li><li>'Oligodendrocyte'</li><li>'OPC'</li><li>'BFCN'</li><li>'GABAergic'</li><li>'Glutamatergic'</li><li>'Doublet'</li></ol>\n",
       "</details>"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item GABAergic\n",
       "\\item Glutamatergic\n",
       "\\item BFCN\n",
       "\\item OPC\n",
       "\\item Oligodendrocyte\n",
       "\\item Astrocyte\n",
       "\\item Microglia\n",
       "\\end{enumerate*}\n",
       "\n",
       "\\emph{Levels}: \\begin{enumerate*}\n",
       "\\item 'Astrocyte'\n",
       "\\item 'Microglia'\n",
       "\\item 'Oligodendrocyte'\n",
       "\\item 'OPC'\n",
       "\\item 'BFCN'\n",
       "\\item 'GABAergic'\n",
       "\\item 'Glutamatergic'\n",
       "\\item 'Doublet'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. GABAergic\n",
       "2. Glutamatergic\n",
       "3. BFCN\n",
       "4. OPC\n",
       "5. Oligodendrocyte\n",
       "6. Astrocyte\n",
       "7. Microglia\n",
       "\n",
       "\n",
       "\n",
       "**Levels**: 1. 'Astrocyte'\n",
       "2. 'Microglia'\n",
       "3. 'Oligodendrocyte'\n",
       "4. 'OPC'\n",
       "5. 'BFCN'\n",
       "6. 'GABAergic'\n",
       "7. 'Glutamatergic'\n",
       "8. 'Doublet'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] GABAergic       Glutamatergic   BFCN            OPC            \n",
       "[5] Oligodendrocyte Astrocyte       Microglia      \n",
       "8 Levels: Astrocyte Microglia Oligodendrocyte OPC BFCN ... Doublet"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"GABAergic\"\n",
      "[1] \"Glutamatergic\"\n",
      "[1] \"BFCN\"\n",
      "[1] \"OPC\"\n",
      "[1] \"Oligodendrocyte\"\n",
      "[1] \"Astrocyte\"\n",
      "[1] \"Microglia\"\n"
     ]
    }
   ],
   "source": [
    "celltypes <- unique(sobj$broad_celltypes)\n",
    "celltypes <- celltypes[! celltypes %in% \"Doublet\"]\n",
    "celltypes\n",
    "\n",
    "for(ct in celltypes){\n",
    "    print(ct)\n",
    "\n",
    "    CT_DIR <- paste0(IDIR, ct, \"/\")\n",
    "    hmapCSV <- list.files(CT_DIR, \"log2fc.+_2.5.+.csv\", full.names = T) # hardcode this to 2.5 or 5\n",
    "    #print(hmapCSV)\n",
    "\n",
    "    # grabbing the tri16 genes that were included in the pct.exp heatmap\n",
    "    hmapGenes <- rownames(read.csv(hmapCSV, row.names = 1))\n",
    "    #print(hmapGenes)\n",
    "\n",
    "    ctsobj <- subset(sobj, subset = broad_celltypes == ct)\n",
    "    DefaultAssay(ctsobj) <- \"SCT\"\n",
    "    ctsobj$conditions <- factor(ctsobj$conditions, levels = c(\"2N_yng\",\"Dp16_yng\",\"2N_old\",\"Dp16_old\"))\n",
    "    \n",
    "    #dplot <- suppressWarnings(Clustered_DotPlot(ctsobj, hmapGenes, group.by = \"conditions\", cluster_ident = FALSE))# + coord_flip() + ggtitle(ct))\n",
    "    dplot <- suppressWarnings(DotPlot(ctsobj, hmapGenes, group.by = \"conditions\") + coord_flip() + ggtitle(ct) + RotatedAxis())\n",
    "\n",
    "    pdf(paste0(CT_DIR,gsub(\".csv\",\"_dplot.pdf\",str_split(hmapCSV, pattern = \"//\")[[1]][2])), width = 6, height = 14)\n",
    "    print(dplot)\n",
    "    dev.off()    \n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5ecbc70-2aac-4666-93a0-260fc46a575f",
   "metadata": {},
   "source": [
    "### dotplot for hmaps with x-axis = celltypes\n",
    "AKA where the directories are the pairwise comparisons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e4849770-b913-4b12-b385-acdacf9103c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "sobj_nodoub$broad_celltypes <- factor(sobj_nodoub$broad_celltypes, levels = c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN',\"GABAergic\",\"Glutamatergic\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "08778c4a-450a-46e9-b62f-aea91c6e97b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"2N_old-2N_yng\"\n",
      "[1] \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/2N_old-2N_yng//log2fc_hmap_2.5pctThres.csv\"\n",
      "[1] \"2N_old\" \"2N_yng\"\n",
      "[1] \"Dp16_old-2N_old\"\n",
      "[1] \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/Dp16_old-2N_old//log2fc_hmap_2.5pctThres.csv\"\n",
      "[1] \"Dp16_old\" \"2N_old\"  \n",
      "[1] \"Dp16_old-2N_yng\"\n",
      "[1] \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/Dp16_old-2N_yng//log2fc_hmap_2.5pctThres.csv\"\n",
      "[1] \"Dp16_old\" \"2N_yng\"  \n",
      "[1] \"Dp16_old-Dp16_yng\"\n",
      "[1] \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/Dp16_old-Dp16_yng//log2fc_hmap_2.5pctThres.csv\"\n",
      "[1] \"Dp16_old\" \"Dp16_yng\"\n",
      "[1] \"Dp16_yng-2N_old\"\n",
      "[1] \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/Dp16_yng-2N_old//log2fc_hmap_2.5pctThres.csv\"\n",
      "[1] \"2N_old\"   \"Dp16_yng\"\n",
      "[1] \"Dp16_yng-2N_yng\"\n",
      "[1] \"/tscc/projects/ps-epigen/users/kdang/ASAP/Aging_Figures/Aging_WWN_nodoub/generalFigures/deseq_tri16_FChmaps/Dp16_yng-2N_yng//log2fc_hmap_2.5pctThres.csv\"\n",
      "[1] \"Dp16_yng\" \"2N_yng\"  \n"
     ]
    }
   ],
   "source": [
    "pairs <- c(\"2N_old-2N_yng\", \"Dp16_old-2N_old\", \"Dp16_old-2N_yng\", \"Dp16_old-Dp16_yng\", \"Dp16_yng-2N_old\", \"Dp16_yng-2N_yng\")\n",
    "for(p in pairs){\n",
    "    print(p)\n",
    "    cond1 <- str_split(p, pattern = \"-\")[[1]][1]\n",
    "    cond2 <- str_split(p, pattern = \"-\")[[1]][2]\n",
    "\n",
    "    PAIR_DIR <- paste0(IDIR, p, \"/\")\n",
    "    hmapCSV <- list.files(PAIR_DIR, \"log2fc.+_2.5.+.csv\", full.names = T) # hardcode this to 2.5 or 5\n",
    "    print(hmapCSV)\n",
    "\n",
    "    # grabbing the tri16 genes that were included in the pct.exp heatmap\n",
    "    hmapGenes <- rownames(read.csv(hmapCSV, row.names = 1))\n",
    "\n",
    "    Idents(sobj_nodoub) <- \"conditions\"\n",
    "    condsobj <- subset(sobj_nodoub, idents = c(cond1, cond2))\n",
    "    DefaultAssay(condsobj) <- \"SCT\" # must be SCT\n",
    "    print(unique(condsobj$conditions))\n",
    "    #condsobj$broad_celltypes <- factor(condsobj$broad_celltypes, levels = c('Astrocyte','Microglia','Oligodendrocyte','OPC','BFCN','GABAergic','Glutamatergic'))\n",
    "\n",
    "    dplot <- suppressWarnings(DotPlot(condsobj, features = hmapGenes, group.by = \"ct_cond\") + RotatedAxis() + coord_flip() + ggtitle(p))\n",
    "    \n",
    "    pdf(paste0(PAIR_DIR,gsub(\".csv\",\"_dplot.pdf\",str_split(hmapCSV, pattern = \"//\")[[1]][2])), width = 12, height = 14)\n",
    "    print(dplot)\n",
    "    dev.off()\n",
    "\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01e4f8f6-6d56-4044-a7f9-3ab767edb489",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b45a2330-13d9-4b06-b89f-b779c7be2967",
   "metadata": {},
   "source": [
    "# testing below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5455350a-fae5-4bba-b683-644df41a65c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "oligo <- subset(sobj, subset = broad_celltypes == \"Oligodendrocyte\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a281cfe7-cbeb-4b3f-b530-2ca6c0326263",
   "metadata": {},
   "outputs": [],
   "source": [
    "DefaultAssay(oligo) <- \"RNA\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "362c26a7-e331-47cb-a4a1-bab095f1e753",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Scaling data with a low number of groups may produce misleading results”\n"
     ]
    },
    {
     "data": {
      "image/png": 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AA0gmAHAACgEQQ7AAAAjSDYAQAAaATB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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ACwBIIdAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEAAACw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vsigVAIAkMWzHy5K6upHLlAFAfu5eTwNB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\nz0FE1HpObJX22f/8qFey9Yi94vb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OwA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\nD3CagUMeEGNVAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# comparing Dp16_old v 2N_old\n",
    "oligo_dplot <- DotPlot(oligo, features = \"Tiam1\", group.by = \"conditions\", scale = T)\n",
    "oligo_dplot\n",
    "\n",
    "DotPlot(oligo, features = \"Tiam1\", group.by = \"replicates\", scale = T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "aff37583-bbaf-435e-8c83-221d05646507",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Tiam1</th><td>0.89813362</td><td>1.8149466</td><td>Tiam1</td><td>Dp16_old</td><td>0.64087110</td></tr>\n",
       "\t<tr><th scope=row>Tiam11</th><td>0.02973206</td><td>0.1909855</td><td>Tiam1</td><td>2N_old  </td><td>0.02929863</td></tr>\n",
       "\t<tr><th scope=row>Tiam12</th><td>0.05341837</td><td>0.5310458</td><td>Tiam1</td><td>Dp16_yng</td><td>0.05204047</td></tr>\n",
       "\t<tr><th scope=row>Tiam13</th><td>0.07297884</td><td>0.7374631</td><td>Tiam1</td><td>2N_yng  </td><td>0.07043874</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tTiam1 & 0.89813362 & 1.8149466 & Tiam1 & Dp16\\_old & 0.64087110\\\\\n",
       "\tTiam11 & 0.02973206 & 0.1909855 & Tiam1 & 2N\\_old   & 0.02929863\\\\\n",
       "\tTiam12 & 0.05341837 & 0.5310458 & Tiam1 & Dp16\\_yng & 0.05204047\\\\\n",
       "\tTiam13 & 0.07297884 & 0.7374631 & Tiam1 & 2N\\_yng   & 0.07043874\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Tiam1 | 0.89813362 | 1.8149466 | Tiam1 | Dp16_old | 0.64087110 |\n",
       "| Tiam11 | 0.02973206 | 0.1909855 | Tiam1 | 2N_old   | 0.02929863 |\n",
       "| Tiam12 | 0.05341837 | 0.5310458 | Tiam1 | Dp16_yng | 0.05204047 |\n",
       "| Tiam13 | 0.07297884 | 0.7374631 | Tiam1 | 2N_yng   | 0.07043874 |\n",
       "\n"
      ],
      "text/plain": [
       "       avg.exp    pct.exp   features.plot id       avg.exp.scaled\n",
       "Tiam1  0.89813362 1.8149466 Tiam1         Dp16_old 0.64087110    \n",
       "Tiam11 0.02973206 0.1909855 Tiam1         2N_old   0.02929863    \n",
       "Tiam12 0.05341837 0.5310458 Tiam1         Dp16_yng 0.05204047    \n",
       "Tiam13 0.07297884 0.7374631 Tiam1         2N_yng   0.07043874    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "oligo_dplot$data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "22cfa68d-3525-4ba4-be7a-6706da8ee108",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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557ZXpi6Y7XZy75dc64/0WfWze0af44V+gKhYsZR6RQsBozqdRju3Xq71qSnTpo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WAwdPITN1N4Ve2kKJ74fD6/3+9yuRI37EJX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\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JVKLpcbFW0FFEUpwVD6Vh0AJCcnezweoVDY8dCOUKlUQqEwKp9RKBSmpqay2Wz6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Ha9nfeTm91UNMItwu6vKjNq93buU+WwMDYN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\nQts6cgCOe2i0xmihR8Ne/T3URbzQWMtsp/VbkXd7327RDQv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jWma7t0l/hvX2dxTNljNzCvx84WHJmK2KCnOMXZrqDnhOu8zyE9f1cpLr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\n2BFCCCGEVBH/B8x8I2j6lUHeAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dplot\n",
    "dplot.data <- dplot$data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "30da03c1-75e9-4b9f-befc-a7a849ab63c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 14 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Tiam1</th><td>4.886727e+08</td><td>77.6181571</td><td>Tiam1</td><td>GABAergic_Dp16_old      </td><td>20.00720355</td></tr>\n",
       "\t<tr><th scope=row>Tiam11</th><td>9.611731e+05</td><td>72.4099723</td><td>Tiam1</td><td>Glutamatergic_Dp16_old  </td><td>13.77591084</td></tr>\n",
       "\t<tr><th scope=row>Tiam12</th><td>3.038221e+07</td><td>81.3559322</td><td>Tiam1</td><td>BFCN_Dp16_old           </td><td>17.22936782</td></tr>\n",
       "\t<tr><th scope=row>Tiam13</th><td>2.055837e+03</td><td>47.0422535</td><td>Tiam1</td><td>OPC_Dp16_old            </td><td> 7.62892443</td></tr>\n",
       "\t<tr><th scope=row>Tiam14</th><td>8.981336e-01</td><td> 1.8149466</td><td>Tiam1</td><td>Oligodendrocyte_Dp16_old</td><td> 0.64087110</td></tr>\n",
       "\t<tr><th scope=row>Tiam15</th><td>1.849033e+03</td><td>30.0632911</td><td>Tiam1</td><td>Astrocyte_Dp16_old      </td><td> 7.52295884</td></tr>\n",
       "\t<tr><th scope=row>Tiam16</th><td>1.071990e+01</td><td> 5.3639847</td><td>Tiam1</td><td>Microglia_Dp16_old      </td><td> 2.46128850</td></tr>\n",
       "\t<tr><th scope=row>Tiam17</th><td>2.862333e+05</td><td>46.4064019</td><td>Tiam1</td><td>GABAergic_2N_old        </td><td>12.56456596</td></tr>\n",
       "\t<tr><th scope=row>Tiam18</th><td>1.449167e+03</td><td>46.9240048</td><td>Tiam1</td><td>Glutamatergic_2N_old    </td><td> 7.27943409</td></tr>\n",
       "\t<tr><th scope=row>Tiam19</th><td>1.073451e+01</td><td>20.9503240</td><td>Tiam1</td><td>OPC_2N_old              </td><td> 2.46253443</td></tr>\n",
       "\t<tr><th scope=row>Tiam110</th><td>9.295479e-01</td><td> 7.8599736</td><td>Tiam1</td><td>Astrocyte_2N_old        </td><td> 0.65728572</td></tr>\n",
       "\t<tr><th scope=row>Tiam111</th><td>3.863828e+00</td><td>36.3636364</td><td>Tiam1</td><td>BFCN_2N_old             </td><td> 1.58182582</td></tr>\n",
       "\t<tr><th scope=row>Tiam112</th><td>2.973206e-02</td><td> 0.1909855</td><td>Tiam1</td><td>Oligodendrocyte_2N_old  </td><td> 0.02929863</td></tr>\n",
       "\t<tr><th scope=row>Tiam113</th><td>4.118398e-02</td><td> 0.5698006</td><td>Tiam1</td><td>Microglia_2N_old        </td><td> 0.04035851</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 14 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tTiam1 & 4.886727e+08 & 77.6181571 & Tiam1 & GABAergic\\_Dp16\\_old       & 20.00720355\\\\\n",
       "\tTiam11 & 9.611731e+05 & 72.4099723 & Tiam1 & Glutamatergic\\_Dp16\\_old   & 13.77591084\\\\\n",
       "\tTiam12 & 3.038221e+07 & 81.3559322 & Tiam1 & BFCN\\_Dp16\\_old            & 17.22936782\\\\\n",
       "\tTiam13 & 2.055837e+03 & 47.0422535 & Tiam1 & OPC\\_Dp16\\_old             &  7.62892443\\\\\n",
       "\tTiam14 & 8.981336e-01 &  1.8149466 & Tiam1 & Oligodendrocyte\\_Dp16\\_old &  0.64087110\\\\\n",
       "\tTiam15 & 1.849033e+03 & 30.0632911 & Tiam1 & Astrocyte\\_Dp16\\_old       &  7.52295884\\\\\n",
       "\tTiam16 & 1.071990e+01 &  5.3639847 & Tiam1 & Microglia\\_Dp16\\_old       &  2.46128850\\\\\n",
       "\tTiam17 & 2.862333e+05 & 46.4064019 & Tiam1 & GABAergic\\_2N\\_old         & 12.56456596\\\\\n",
       "\tTiam18 & 1.449167e+03 & 46.9240048 & Tiam1 & Glutamatergic\\_2N\\_old     &  7.27943409\\\\\n",
       "\tTiam19 & 1.073451e+01 & 20.9503240 & Tiam1 & OPC\\_2N\\_old               &  2.46253443\\\\\n",
       "\tTiam110 & 9.295479e-01 &  7.8599736 & Tiam1 & Astrocyte\\_2N\\_old         &  0.65728572\\\\\n",
       "\tTiam111 & 3.863828e+00 & 36.3636364 & Tiam1 & BFCN\\_2N\\_old              &  1.58182582\\\\\n",
       "\tTiam112 & 2.973206e-02 &  0.1909855 & Tiam1 & Oligodendrocyte\\_2N\\_old   &  0.02929863\\\\\n",
       "\tTiam113 & 4.118398e-02 &  0.5698006 & Tiam1 & Microglia\\_2N\\_old         &  0.04035851\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 14 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Tiam1 | 4.886727e+08 | 77.6181571 | Tiam1 | GABAergic_Dp16_old       | 20.00720355 |\n",
       "| Tiam11 | 9.611731e+05 | 72.4099723 | Tiam1 | Glutamatergic_Dp16_old   | 13.77591084 |\n",
       "| Tiam12 | 3.038221e+07 | 81.3559322 | Tiam1 | BFCN_Dp16_old            | 17.22936782 |\n",
       "| Tiam13 | 2.055837e+03 | 47.0422535 | Tiam1 | OPC_Dp16_old             |  7.62892443 |\n",
       "| Tiam14 | 8.981336e-01 |  1.8149466 | Tiam1 | Oligodendrocyte_Dp16_old |  0.64087110 |\n",
       "| Tiam15 | 1.849033e+03 | 30.0632911 | Tiam1 | Astrocyte_Dp16_old       |  7.52295884 |\n",
       "| Tiam16 | 1.071990e+01 |  5.3639847 | Tiam1 | Microglia_Dp16_old       |  2.46128850 |\n",
       "| Tiam17 | 2.862333e+05 | 46.4064019 | Tiam1 | GABAergic_2N_old         | 12.56456596 |\n",
       "| Tiam18 | 1.449167e+03 | 46.9240048 | Tiam1 | Glutamatergic_2N_old     |  7.27943409 |\n",
       "| Tiam19 | 1.073451e+01 | 20.9503240 | Tiam1 | OPC_2N_old               |  2.46253443 |\n",
       "| Tiam110 | 9.295479e-01 |  7.8599736 | Tiam1 | Astrocyte_2N_old         |  0.65728572 |\n",
       "| Tiam111 | 3.863828e+00 | 36.3636364 | Tiam1 | BFCN_2N_old              |  1.58182582 |\n",
       "| Tiam112 | 2.973206e-02 |  0.1909855 | Tiam1 | Oligodendrocyte_2N_old   |  0.02929863 |\n",
       "| Tiam113 | 4.118398e-02 |  0.5698006 | Tiam1 | Microglia_2N_old         |  0.04035851 |\n",
       "\n"
      ],
      "text/plain": [
       "        avg.exp      pct.exp    features.plot id                      \n",
       "Tiam1   4.886727e+08 77.6181571 Tiam1         GABAergic_Dp16_old      \n",
       "Tiam11  9.611731e+05 72.4099723 Tiam1         Glutamatergic_Dp16_old  \n",
       "Tiam12  3.038221e+07 81.3559322 Tiam1         BFCN_Dp16_old           \n",
       "Tiam13  2.055837e+03 47.0422535 Tiam1         OPC_Dp16_old            \n",
       "Tiam14  8.981336e-01  1.8149466 Tiam1         Oligodendrocyte_Dp16_old\n",
       "Tiam15  1.849033e+03 30.0632911 Tiam1         Astrocyte_Dp16_old      \n",
       "Tiam16  1.071990e+01  5.3639847 Tiam1         Microglia_Dp16_old      \n",
       "Tiam17  2.862333e+05 46.4064019 Tiam1         GABAergic_2N_old        \n",
       "Tiam18  1.449167e+03 46.9240048 Tiam1         Glutamatergic_2N_old    \n",
       "Tiam19  1.073451e+01 20.9503240 Tiam1         OPC_2N_old              \n",
       "Tiam110 9.295479e-01  7.8599736 Tiam1         Astrocyte_2N_old        \n",
       "Tiam111 3.863828e+00 36.3636364 Tiam1         BFCN_2N_old             \n",
       "Tiam112 2.973206e-02  0.1909855 Tiam1         Oligodendrocyte_2N_old  \n",
       "Tiam113 4.118398e-02  0.5698006 Tiam1         Microglia_2N_old        \n",
       "        avg.exp.scaled\n",
       "Tiam1   20.00720355   \n",
       "Tiam11  13.77591084   \n",
       "Tiam12  17.22936782   \n",
       "Tiam13   7.62892443   \n",
       "Tiam14   0.64087110   \n",
       "Tiam15   7.52295884   \n",
       "Tiam16   2.46128850   \n",
       "Tiam17  12.56456596   \n",
       "Tiam18   7.27943409   \n",
       "Tiam19   2.46253443   \n",
       "Tiam110  0.65728572   \n",
       "Tiam111  1.58182582   \n",
       "Tiam112  0.02929863   \n",
       "Tiam113  0.04035851   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tiam1 <- dplot.data[dplot.data$features.plot == \"Tiam1\",]\n",
    "tiam1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a1ab2d38-7ed2-4c31-ab3e-79221f1c5263",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Rbm11</th><td>2.604465e-01</td><td> 9.1720503</td><td>Rbm11 </td><td>GABAergic_Dp16_old</td><td> 0.2314660</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>5.163378e-01</td><td>17.8850731</td><td>Hspa13</td><td>GABAergic_Dp16_old</td><td> 0.4162981</td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td>1.113509e-01</td><td> 0.5015301</td><td>Samsn1</td><td>GABAergic_Dp16_old</td><td> 0.1055763</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td>2.293252e+06</td><td>31.8259096</td><td>Nrip1 </td><td>GABAergic_Dp16_old</td><td>14.6454820</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td>7.815903e+01</td><td>43.5056103</td><td>Usp25 </td><td>GABAergic_Dp16_old</td><td> 4.3714589</td></tr>\n",
       "\t<tr><th scope=row>Cxadr</th><td>5.376255e+00</td><td>40.8364502</td><td>Cxadr </td><td>GABAergic_Dp16_old</td><td> 1.8525809</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tRbm11 & 2.604465e-01 &  9.1720503 & Rbm11  & GABAergic\\_Dp16\\_old &  0.2314660\\\\\n",
       "\tHspa13 & 5.163378e-01 & 17.8850731 & Hspa13 & GABAergic\\_Dp16\\_old &  0.4162981\\\\\n",
       "\tSamsn1 & 1.113509e-01 &  0.5015301 & Samsn1 & GABAergic\\_Dp16\\_old &  0.1055763\\\\\n",
       "\tNrip1 & 2.293252e+06 & 31.8259096 & Nrip1  & GABAergic\\_Dp16\\_old & 14.6454820\\\\\n",
       "\tUsp25 & 7.815903e+01 & 43.5056103 & Usp25  & GABAergic\\_Dp16\\_old &  4.3714589\\\\\n",
       "\tCxadr & 5.376255e+00 & 40.8364502 & Cxadr  & GABAergic\\_Dp16\\_old &  1.8525809\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Rbm11 | 2.604465e-01 |  9.1720503 | Rbm11  | GABAergic_Dp16_old |  0.2314660 |\n",
       "| Hspa13 | 5.163378e-01 | 17.8850731 | Hspa13 | GABAergic_Dp16_old |  0.4162981 |\n",
       "| Samsn1 | 1.113509e-01 |  0.5015301 | Samsn1 | GABAergic_Dp16_old |  0.1055763 |\n",
       "| Nrip1 | 2.293252e+06 | 31.8259096 | Nrip1  | GABAergic_Dp16_old | 14.6454820 |\n",
       "| Usp25 | 7.815903e+01 | 43.5056103 | Usp25  | GABAergic_Dp16_old |  4.3714589 |\n",
       "| Cxadr | 5.376255e+00 | 40.8364502 | Cxadr  | GABAergic_Dp16_old |  1.8525809 |\n",
       "\n"
      ],
      "text/plain": [
       "       avg.exp      pct.exp    features.plot id                 avg.exp.scaled\n",
       "Rbm11  2.604465e-01  9.1720503 Rbm11         GABAergic_Dp16_old  0.2314660    \n",
       "Hspa13 5.163378e-01 17.8850731 Hspa13        GABAergic_Dp16_old  0.4162981    \n",
       "Samsn1 1.113509e-01  0.5015301 Samsn1        GABAergic_Dp16_old  0.1055763    \n",
       "Nrip1  2.293252e+06 31.8259096 Nrip1         GABAergic_Dp16_old 14.6454820    \n",
       "Usp25  7.815903e+01 43.5056103 Usp25         GABAergic_Dp16_old  4.3714589    \n",
       "Cxadr  5.376255e+00 40.8364502 Cxadr         GABAergic_Dp16_old  1.8525809    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(dplot.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "797e6173-d7a0-453d-a93d-5c5c22af72d1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e0e7c6e-c8fa-42bd-99ee-f1cfc010913b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a015919f-d3c0-4c32-9b6f-1f52ea84a2ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dp16_old v Dp16_yng\n",
    "# glut Dscam\n",
    "glut <- subset(sobj, subset = broad_celltypes == \"Glutamatergic\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "95717163-ad14-4c83-97dd-c6b9e6390326",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'orig.ident'</li><li>'nCount_RNA'</li><li>'nFeature_RNA'</li><li>'nCount_ATAC'</li><li>'nFeature_ATAC'</li><li>'percent.mt'</li><li>'nCount_SCT'</li><li>'nFeature_SCT'</li><li>'nCount_ATAC_COMB'</li><li>'nFeature_ATAC_COMB'</li><li>'SCT_snn_res.0.5'</li><li>'seurat_clusters'</li><li>'conditions'</li><li>'SCT_snn_res.0.05'</li><li>'TSS.enrichment'</li><li>'TSS.percentile'</li><li>'DF.classification'</li><li>'DF.scores'</li><li>'age'</li><li>'genotype'</li><li>'blacklist_fraction'</li><li>'SCT_snn_res.1.2'</li><li>'ATAC_snn_res.1.2'</li><li>'SCT.weight'</li><li>'ATAC.weight'</li><li>'wsnn_res.1.2'</li><li>'qn.DF.scores'</li><li>'ATAC_COMB_snn_res.1.2'</li><li>'ATAC_COMB.weight'</li><li>'nCount_cpeaks'</li><li>'nFeature_cpeaks'</li><li>'cpeaks_snn_res.1.2'</li><li>'cpeaks.weight'</li><li>'broad_celltypes'</li><li>'sub_celltypes'</li><li>'sub_celltypes_v2'</li><li>'frozenBatch'</li><li>'nCount_macs3_peaks'</li><li>'nFeature_macs3_peaks'</li><li>'replicates'</li><li>'ct_cond'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'orig.ident'\n",
       "\\item 'nCount\\_RNA'\n",
       "\\item 'nFeature\\_RNA'\n",
       "\\item 'nCount\\_ATAC'\n",
       "\\item 'nFeature\\_ATAC'\n",
       "\\item 'percent.mt'\n",
       "\\item 'nCount\\_SCT'\n",
       "\\item 'nFeature\\_SCT'\n",
       "\\item 'nCount\\_ATAC\\_COMB'\n",
       "\\item 'nFeature\\_ATAC\\_COMB'\n",
       "\\item 'SCT\\_snn\\_res.0.5'\n",
       "\\item 'seurat\\_clusters'\n",
       "\\item 'conditions'\n",
       "\\item 'SCT\\_snn\\_res.0.05'\n",
       "\\item 'TSS.enrichment'\n",
       "\\item 'TSS.percentile'\n",
       "\\item 'DF.classification'\n",
       "\\item 'DF.scores'\n",
       "\\item 'age'\n",
       "\\item 'genotype'\n",
       "\\item 'blacklist\\_fraction'\n",
       "\\item 'SCT\\_snn\\_res.1.2'\n",
       "\\item 'ATAC\\_snn\\_res.1.2'\n",
       "\\item 'SCT.weight'\n",
       "\\item 'ATAC.weight'\n",
       "\\item 'wsnn\\_res.1.2'\n",
       "\\item 'qn.DF.scores'\n",
       "\\item 'ATAC\\_COMB\\_snn\\_res.1.2'\n",
       "\\item 'ATAC\\_COMB.weight'\n",
       "\\item 'nCount\\_cpeaks'\n",
       "\\item 'nFeature\\_cpeaks'\n",
       "\\item 'cpeaks\\_snn\\_res.1.2'\n",
       "\\item 'cpeaks.weight'\n",
       "\\item 'broad\\_celltypes'\n",
       "\\item 'sub\\_celltypes'\n",
       "\\item 'sub\\_celltypes\\_v2'\n",
       "\\item 'frozenBatch'\n",
       "\\item 'nCount\\_macs3\\_peaks'\n",
       "\\item 'nFeature\\_macs3\\_peaks'\n",
       "\\item 'replicates'\n",
       "\\item 'ct\\_cond'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'orig.ident'\n",
       "2. 'nCount_RNA'\n",
       "3. 'nFeature_RNA'\n",
       "4. 'nCount_ATAC'\n",
       "5. 'nFeature_ATAC'\n",
       "6. 'percent.mt'\n",
       "7. 'nCount_SCT'\n",
       "8. 'nFeature_SCT'\n",
       "9. 'nCount_ATAC_COMB'\n",
       "10. 'nFeature_ATAC_COMB'\n",
       "11. 'SCT_snn_res.0.5'\n",
       "12. 'seurat_clusters'\n",
       "13. 'conditions'\n",
       "14. 'SCT_snn_res.0.05'\n",
       "15. 'TSS.enrichment'\n",
       "16. 'TSS.percentile'\n",
       "17. 'DF.classification'\n",
       "18. 'DF.scores'\n",
       "19. 'age'\n",
       "20. 'genotype'\n",
       "21. 'blacklist_fraction'\n",
       "22. 'SCT_snn_res.1.2'\n",
       "23. 'ATAC_snn_res.1.2'\n",
       "24. 'SCT.weight'\n",
       "25. 'ATAC.weight'\n",
       "26. 'wsnn_res.1.2'\n",
       "27. 'qn.DF.scores'\n",
       "28. 'ATAC_COMB_snn_res.1.2'\n",
       "29. 'ATAC_COMB.weight'\n",
       "30. 'nCount_cpeaks'\n",
       "31. 'nFeature_cpeaks'\n",
       "32. 'cpeaks_snn_res.1.2'\n",
       "33. 'cpeaks.weight'\n",
       "34. 'broad_celltypes'\n",
       "35. 'sub_celltypes'\n",
       "36. 'sub_celltypes_v2'\n",
       "37. 'frozenBatch'\n",
       "38. 'nCount_macs3_peaks'\n",
       "39. 'nFeature_macs3_peaks'\n",
       "40. 'replicates'\n",
       "41. 'ct_cond'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"orig.ident\"            \"nCount_RNA\"            \"nFeature_RNA\"         \n",
       " [4] \"nCount_ATAC\"           \"nFeature_ATAC\"         \"percent.mt\"           \n",
       " [7] \"nCount_SCT\"            \"nFeature_SCT\"          \"nCount_ATAC_COMB\"     \n",
       "[10] \"nFeature_ATAC_COMB\"    \"SCT_snn_res.0.5\"       \"seurat_clusters\"      \n",
       "[13] \"conditions\"            \"SCT_snn_res.0.05\"      \"TSS.enrichment\"       \n",
       "[16] \"TSS.percentile\"        \"DF.classification\"     \"DF.scores\"            \n",
       "[19] \"age\"                   \"genotype\"              \"blacklist_fraction\"   \n",
       "[22] \"SCT_snn_res.1.2\"       \"ATAC_snn_res.1.2\"      \"SCT.weight\"           \n",
       "[25] \"ATAC.weight\"           \"wsnn_res.1.2\"          \"qn.DF.scores\"         \n",
       "[28] \"ATAC_COMB_snn_res.1.2\" \"ATAC_COMB.weight\"      \"nCount_cpeaks\"        \n",
       "[31] \"nFeature_cpeaks\"       \"cpeaks_snn_res.1.2\"    \"cpeaks.weight\"        \n",
       "[34] \"broad_celltypes\"       \"sub_celltypes\"         \"sub_celltypes_v2\"     \n",
       "[37] \"frozenBatch\"           \"nCount_macs3_peaks\"    \"nFeature_macs3_peaks\" \n",
       "[40] \"replicates\"            \"ct_cond\"              "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DefaultAssay(glut) <- \"SCT\"\n",
    "colnames(glut@meta.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "c6a1e575-467c-4e0d-bc75-9db0817ea09d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 12 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Dscam</th><td>7.324405</td><td>99.10714</td><td>Dscam</td><td>Dp16_old_Rep1</td><td> 1.53776278</td></tr>\n",
       "\t<tr><th scope=row>Dscam1</th><td>6.716084</td><td>95.80420</td><td>Dscam</td><td>Dp16_old_Rep2</td><td> 1.29228947</td></tr>\n",
       "\t<tr><th scope=row>Dscam2</th><td>6.375598</td><td>96.65072</td><td>Dscam</td><td>Dp16_old_Rep3</td><td> 1.14630189</td></tr>\n",
       "\t<tr><th scope=row>Dscam3</th><td>3.367983</td><td>90.74844</td><td>Dscam</td><td>2N_old_Rep1  </td><td>-0.54834402</td></tr>\n",
       "\t<tr><th scope=row>Dscam4</th><td>2.558324</td><td>80.63420</td><td>Dscam</td><td>2N_old_Rep2  </td><td>-1.21152141</td></tr>\n",
       "\t<tr><th scope=row>Dscam5</th><td>3.347352</td><td>86.91589</td><td>Dscam</td><td>2N_old_Rep3  </td><td>-0.56365930</td></tr>\n",
       "\t<tr><th scope=row>Dscam6</th><td>4.063063</td><td>89.83269</td><td>Dscam</td><td>Dp16_yng_Rep1</td><td>-0.07065667</td></tr>\n",
       "\t<tr><th scope=row>Dscam7</th><td>4.683143</td><td>94.16984</td><td>Dscam</td><td>Dp16_yng_Rep2</td><td> 0.30307180</td></tr>\n",
       "\t<tr><th scope=row>Dscam8</th><td>5.613712</td><td>95.65217</td><td>Dscam</td><td>Dp16_yng_Rep3</td><td> 0.79360285</td></tr>\n",
       "\t<tr><th scope=row>Dscam9</th><td>2.868941</td><td>80.78995</td><td>Dscam</td><td>2N_yng_Rep1  </td><td>-0.94079518</td></tr>\n",
       "\t<tr><th scope=row>Dscam10</th><td>2.420161</td><td>78.79032</td><td>Dscam</td><td>2N_yng_Rep2  </td><td>-1.33962666</td></tr>\n",
       "\t<tr><th scope=row>Dscam11</th><td>3.575182</td><td>90.51095</td><td>Dscam</td><td>2N_yng_Rep3  </td><td>-0.39842554</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 12 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tDscam & 7.324405 & 99.10714 & Dscam & Dp16\\_old\\_Rep1 &  1.53776278\\\\\n",
       "\tDscam1 & 6.716084 & 95.80420 & Dscam & Dp16\\_old\\_Rep2 &  1.29228947\\\\\n",
       "\tDscam2 & 6.375598 & 96.65072 & Dscam & Dp16\\_old\\_Rep3 &  1.14630189\\\\\n",
       "\tDscam3 & 3.367983 & 90.74844 & Dscam & 2N\\_old\\_Rep1   & -0.54834402\\\\\n",
       "\tDscam4 & 2.558324 & 80.63420 & Dscam & 2N\\_old\\_Rep2   & -1.21152141\\\\\n",
       "\tDscam5 & 3.347352 & 86.91589 & Dscam & 2N\\_old\\_Rep3   & -0.56365930\\\\\n",
       "\tDscam6 & 4.063063 & 89.83269 & Dscam & Dp16\\_yng\\_Rep1 & -0.07065667\\\\\n",
       "\tDscam7 & 4.683143 & 94.16984 & Dscam & Dp16\\_yng\\_Rep2 &  0.30307180\\\\\n",
       "\tDscam8 & 5.613712 & 95.65217 & Dscam & Dp16\\_yng\\_Rep3 &  0.79360285\\\\\n",
       "\tDscam9 & 2.868941 & 80.78995 & Dscam & 2N\\_yng\\_Rep1   & -0.94079518\\\\\n",
       "\tDscam10 & 2.420161 & 78.79032 & Dscam & 2N\\_yng\\_Rep2   & -1.33962666\\\\\n",
       "\tDscam11 & 3.575182 & 90.51095 & Dscam & 2N\\_yng\\_Rep3   & -0.39842554\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 12 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Dscam | 7.324405 | 99.10714 | Dscam | Dp16_old_Rep1 |  1.53776278 |\n",
       "| Dscam1 | 6.716084 | 95.80420 | Dscam | Dp16_old_Rep2 |  1.29228947 |\n",
       "| Dscam2 | 6.375598 | 96.65072 | Dscam | Dp16_old_Rep3 |  1.14630189 |\n",
       "| Dscam3 | 3.367983 | 90.74844 | Dscam | 2N_old_Rep1   | -0.54834402 |\n",
       "| Dscam4 | 2.558324 | 80.63420 | Dscam | 2N_old_Rep2   | -1.21152141 |\n",
       "| Dscam5 | 3.347352 | 86.91589 | Dscam | 2N_old_Rep3   | -0.56365930 |\n",
       "| Dscam6 | 4.063063 | 89.83269 | Dscam | Dp16_yng_Rep1 | -0.07065667 |\n",
       "| Dscam7 | 4.683143 | 94.16984 | Dscam | Dp16_yng_Rep2 |  0.30307180 |\n",
       "| Dscam8 | 5.613712 | 95.65217 | Dscam | Dp16_yng_Rep3 |  0.79360285 |\n",
       "| Dscam9 | 2.868941 | 80.78995 | Dscam | 2N_yng_Rep1   | -0.94079518 |\n",
       "| Dscam10 | 2.420161 | 78.79032 | Dscam | 2N_yng_Rep2   | -1.33962666 |\n",
       "| Dscam11 | 3.575182 | 90.51095 | Dscam | 2N_yng_Rep3   | -0.39842554 |\n",
       "\n"
      ],
      "text/plain": [
       "        avg.exp  pct.exp  features.plot id            avg.exp.scaled\n",
       "Dscam   7.324405 99.10714 Dscam         Dp16_old_Rep1  1.53776278   \n",
       "Dscam1  6.716084 95.80420 Dscam         Dp16_old_Rep2  1.29228947   \n",
       "Dscam2  6.375598 96.65072 Dscam         Dp16_old_Rep3  1.14630189   \n",
       "Dscam3  3.367983 90.74844 Dscam         2N_old_Rep1   -0.54834402   \n",
       "Dscam4  2.558324 80.63420 Dscam         2N_old_Rep2   -1.21152141   \n",
       "Dscam5  3.347352 86.91589 Dscam         2N_old_Rep3   -0.56365930   \n",
       "Dscam6  4.063063 89.83269 Dscam         Dp16_yng_Rep1 -0.07065667   \n",
       "Dscam7  4.683143 94.16984 Dscam         Dp16_yng_Rep2  0.30307180   \n",
       "Dscam8  5.613712 95.65217 Dscam         Dp16_yng_Rep3  0.79360285   \n",
       "Dscam9  2.868941 80.78995 Dscam         2N_yng_Rep1   -0.94079518   \n",
       "Dscam10 2.420161 78.79032 Dscam         2N_yng_Rep2   -1.33962666   \n",
       "Dscam11 3.575182 90.51095 Dscam         2N_yng_Rep3   -0.39842554   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Scaling data with a low number of groups may produce misleading results”\n"
     ]
    },
    {
     "data": {
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3ELZurN47t3x3x6/Txk93MiImqgNfFTsCPS67c34ort4t+2nbq4PzKDVPRb9Zm2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iTzs1Qp2MRoN79+DWLVi/Ht6/b7aalRV4\neAC+mIgQQi1r9Rm7zJjA6AwAipzBaG2pnx9bI6Nvrdd4/4U/XfGHZy8/lTd7mE9xkLFqh67y\n8lucujPhM3aIUU0NPH8Od+9CTAxkZEB+PkhJgYICDBsG48aBqmpXx4cQQn+CVhO7m5NJU24B\nUB1uV1we//NjaybdIG5O7qAQUXeFiR1CCCHUsVqdihVT0dPTA6AqizJ+bI2KWOt1EEIIIYRQ\nR2o1sTP3YFqNoNFHhBBCCCH0u+j4PV0RQgghhFCX4DSxizvl4rL8QkLzFUrD9ru4uJyKa1dU\nCCGEEEKIY5wmdinB3t5nQptfeQPK39z19vYOTmlXVAghhBBCiGMdPhVLp9MBSGSc4kUIIYQQ\n+sU6PAH78iUdQEjoD1xVDSGEEELoz8bWzhOlHyNefCwBAICEbICajPh//+VtUouoLvue8ujY\n2VSAwVq4PjxCCCGE0C/GVmKXenHu8K1vGz4Hbxwe3EJ1sYmLp/VsZ1wIIYQQQohDbCV2vD16\n12/RWPTl7ZcSEQUN2SZzrSQKDz9Nprf+8BmLF4yU6tgoEUIIIYRQq9hK7FQX3n6zsPY/b04m\nTXkw7tib89adGRVCCCGEEOIYW4kdA4PFPj4TVLU7JRaEEEIIIdQOnCZ2vYbNnNkZcSCEEEII\noXbC9eYQQgghhLoJTu/YAQAAkf/mzqXL957Ef8jIL/lRTRBNalh4RnuYtzs4hBBCCCHEPs4T\nu7JYD5vR60Oy6S1VUsxrc0QIIYQQQqhNOE3s6NHb7NeFZAO31CD7ufZD1OWlRakspnNl9Dsk\nOoQQQgghxDZOE7tX16+/B5Cyuxp/bRIuVocQQggh9Bvh9OWJ9PR0APHxLpjVIYQQQgjBpz36\nJBKJd2ZgVwcCAJwnduLi4gASEhKdEgxCCCHUZV5t6EMikUgkkv6e910dy++s4rw1qUWjzpd0\ndYx/MU6nYvVHjBA76hsZ+R20xDslIIQQQqgL0J+dvZhU+58xPj6v1+3q37Xx/PZIvMJiAtys\njtB4Sb86mC4lqDXGwaEPz2C5rg4EADhP7KhWWzyG3523bfnNkT6TZdu0WApCCCH0u6kM9vFN\nBxAQEaksKEi+6PNs+wFjSlcH9VsTc7qVe9Kyq6P4HUhYb7v8+2y0ymlqlpeSpbVmj9Oi5VM0\n4qYsW2Cjp64kLdi0E3E1w95iHRMhQggh1NlK/c9dzwMQm3zMs2Du3DtfL58L9jQezfJ+FEK/\nM06fsQtxMzIa7nIhuQKK397YsdhxwnATIxbcQjolWoQQQqgT5N04d7cYoIedo+1UpwlCALnX\nz90tZajwca8emUSiDD6czqL1j3uzREkkkrRLWDVjcUnSHQ9nm0Gq0iJ8PLzCPVQNxy89Fv61\niqlptKsiiUSSc42A8ne3Ns8w6ysrxs9Fkl4cVnu4MPnhBY/ltuZ6GopSwrw8fDRpNaNxiw88\n/PyDRRj03Jcnl9ro9hLjp/KLy/cf5XLgcSY996QliUQijb9c3bg6O+G1U/mz1ZrcJBJF2flR\nIfOR9EvW4iQSSdDscHL9srgNl6Lo1cXVkwxVegjz8gn31DSf7fHgS2Wjnlu5bmyOjihM8N3k\naDFAUUKQyk0VkpRT0TKynu12IOQLR3WaeXmiPDXIa4G1gWoPGi8Pn4iMmtHEZUfC0huNpGEg\nlZ/u7XQy05AR4aMKSKoOsl1/I7mc/UvNOCrOBC3oxY4FQRz2i/5Ctra2AJCWltbVgSCE/nbp\nh03JAKCwPIJOEJXBsyUAgMfKJ5ehyreDQygAoLf7fZPWpddthQCg14pn9J9lP5LO2SpzAwCQ\neMUUtHT69RLlAQAgSZjtjS5vaBu1qhcAyC48tFVPAACoIj3lZcX5pBc8qj18dRIAAIVXREa5\nr56BTp9e4rWPr4kO2R1bwRQE/fN1u14UAACKiJKOoaGuihgXkGUmHNpgDgAw7lIVY212w2Op\n3McKAEDc+WHrV7YyYYcBLwDI2F7P+llYnXzAVBAAxK190ptcivkeqzWpQOLvqTnQ0EC9Bw8A\nAIib7XvNFFaL143N0RWGLOlDBQAgC8lqaA8yMtBSlqFRSQBgd4OTOkTqbj0AoDoFMASY9WDx\nAAEAAOCVUtfV11EVrx2JiOGWJ/lNB7L4pNcQEQAuYTk1dUUxau0ziqLDT6TQCU5xmtgh1GEw\nsUMI/R4+7NAmAYDa+liCIAii5vESOQCgmBz6xlAp+/RIbgDouymxUevCKza8AKC6Ie5nUUno\nUjUyAFlh9M77qfUJWFH8OScNXgBSr2WPf2YXtd/r3FQql5y1R0haGZ0gCKIiO6eo9nDctb2+\nYe8Lq3/2TC9MCnQzEQEga22OZwji8zEzQQDg11kS8KnuhJXpD9caCXNzczdJ7NgPjyVOEjuC\nqEk5YSYMALRRp1LpBEEQP2K36PEAQM9pd3IYK9ZeCi4uLkqvySdfF9ZmNDXZz/ZYSAAAWWPt\ny8rGlVleN3ZH93HvIACg9l8S9IVhvOVfI657XX9FsF+HVWKXfmYUDQAoSlNOxeXXjqQ6+7nH\nSCkAgB52txt+ZagdCA8vL6+ag3d0bu3fdEXyP7PUuABAeLp/KTsXmREmdqjLYGKHEPotxK1X\nBQDot/NdXQE9xk0ZAGDA7mSGaoVXbPgAQHldNNNdlJzahK/f1qSfRR/3GVAAuLQ2RjXKkKrj\nt+pQAHitfOpv2tR+rwOor47+wXbAGUeMAUBhZWR9QU2Eay8A4Bl8OJW55rezw/mhcWLHQXgs\n1SV2zWp0d5AgvvpOlAAAfsO9b6uKw1eoUQDIyotDCplr1V8KqTkPmePKuTROAAAExl8raFK5\n6XVje3T359AAwNDrUwtDZadO08SOHrlGEQBAbmk4c3BF/vZiAEDS3vFfo4GQ+66PY7pqpf7T\nxQFAdO6DFk/NAqfP2DGjVxbnZX1Nz2vbLDBCCCHU1ejh5y5+ACANcpyuXldE0nVy7AcA8T7n\n4xoqCk9wGicM8PHKpWdEQ2nm1Uv/VgFpkOMMtfqiNL8bUTUAhnMX6fMyn4vS38GuH0BFWMhz\n5g3XB81dqMfTTICV2XGB57zcVy6cN8txxvTp06dPd/XP4gb4HBOTW1cl8f79NACu4fNmKjK3\nlXGYZ83fqL82hMcSiVdYnCXhxqud9Jx65vwsBSiLWG9rM97hYHIN9wC3q15mwiy77eu8zJI5\nLgn7ZQ49AEqDg8IbPyjY9LqxPzoFBQUAeHPnUkwhAc1gp05Tb+/d+wQA+otXmjAHJzR2tbMa\nAPHqXtA35iamC5dqM72Jym9iogsA+R8+sH/eWm1bsKTmW7j3bs8zt8Piv5bSASbdIG5OBgAo\n+nfPssvvFO29No/CJYwRQgj9/iqDz/mmA1DMnBwUGkrVnZwMt7pGJF8492zbkfplT/hsHCeL\nXTv35erFUK8h5rXfn5+uXHxSAxQTRweln43j4+MBgJoTtG4mQ15Yi0j9DgCl6ekFAA2LRwgP\nGKDIMrqiCK+p9huD0li9KwHfv38HkAAASEpKBgDlAQOEGtehamv3geuxjEWch8caJ8udiFod\n8V3+fOjBtw8eAfAb7bi2ZSCVdU2ypmafxmVcffuqAWSX/fffZ7BRZjjA4rqxP7q+c1aPOegY\n9MTdoKe3gcWIYUMGGw8ZajpIVYRhlRt26jRV+9chqKXVq/ERklY/LTIk09+9ewfQs6Gcpq7e\neEMvMWlpboCqEo7Xem5DYlce42U1ak1oLovkVVhTOO3Shcs5Q5eOmiXKec8IIYTQL1Xsf+7m\ndwCe4Y52Mozlig5OpusiHn/1PRfsZTy6LgnhGeFkJ3PuRMaNS/87Ym5FBYB3ly9FE8Az3Mm+\nofWP/PxyAPiRFHwhqbnTlpWVMWZOQkJNMjIAgO83ZlmtDsrjVrf12L54zCANRSkRfioXGSBk\nvpjF6fyqqrqXPCuKi6sAQFiYxT2wJl23IbyOINDP0kj6YNJXAB7T2TP7NJt9iElJNV1kpoeU\nFBmAXlxczFze9LpxMjrZGTdfCntu9TznHxEZcC4y4BwA8PTQm+K6d98qM6naGU126jRW99ch\nLS3d9BiPjIwowPfGIxEUFGxSlUwmAwDBwZ3CunacNqh4vHbC6tBcqtLYrTejPuTccBRgPCoz\nYYIhVD8KuF/Gab8IIYTQr5Z33eduKQBUPpgpzrwtlsyCx9W1Fe40LHtCMXGcpgRQcOvi3TIA\ngISLl+IB+KwdpzBkQVRBQW4AUF4T2fxzUBHL2dilIOv6ydt5AAO3P7i6ZoqJloKEIJWLDABQ\n9f17EWNFXiEhbgAoKipq2kmTZKjDwuNItt+Cuee/AplMhsoHa2ddTG8uX8nLymqyMAtkZ2XR\nodn8lxFno+PrPW7z5Wdp+d8/RN6/uG/t9KGKXNkxV9aMHrsn4WcQ7NRhVvfXkZWZ2fRYZUZG\nPnsjaTNOE7uSG/tPfQGa1YnwO5sm6atINJ5IlzEwkIUfSUlpHRYhQggh1Dm+XjkX/AOAS1BC\nigUJQS6Akjvnbnz/2YBk6DRDHaD47iX/QiBeXrySDCA8znE8062yfv20ACD16dNvjc/HmfdJ\nSQSAwhBTRebvanrk85c1TCXq6moA8DE+vsm83Y/4+HeNijoqPPYRn32c5vpmgpDFkdAzNuKQ\nF7TI4dD7GpZ16YmJjQOGmsTEZADg19BQYNGCWVtGxy2iYjBqxso9l8KSY/YO4YEfkacuvGpD\nnXp9+qgDQPGbN01zobdv3tIBQEOjyXxzh+E0sYt5/vwHiNmunNlcMi8jIwPw7dsv+3FBCCGE\n2ibp/LnndIAes+5kZLLw9eZ0cYDKh+euMKxK3M9xhjZAxYOLNzLDLvp+BpCY7DiGj6lbtUm2\nA8hAPD+0/RGLW2jso1KpAJD77RvzmrbZVzwvfGWu2Xf0aK4VMmQAACAASURBVAWA6odnz39m\nPpB59Uxg4ym0jgqPXTXJ+x2WPMgHyfHHLy00neXj4yALJeFrp+6Ia7zqMAAAvPU+9Ij5kcK8\na4evZAPwDx9t2vrzY+0bHXefYcYy0HIa03qdvlZWigAQfXT/E+YhlgR4eScBkHSsRvdk2bIj\ncJrYFRYWAvRSVGy2Ap1OB6ioqGhXVAghhFBni/c5/woAek2fZcYyYeAZPmuaHAD9ic8FhlcT\nVWY4GZOg6t9z8/b+8w1A2t5xROOHwtQX71/UmwJpJydbLrsc971hxo4oz3gVeHz1tD3h7MTX\n39RUBKDs5qblAWl1CUL5x9vLrBbcK+dlDpg8aMlaMwGofLpu0oqgz3V1q76FbJi8PKSyySNr\nHRQeeypjttqvf1pKknM8f3a6DACI25y4vESFXBmz3d7tSdM3A7i4cn3mO515U1w7V0vPjfCy\nX+FfCmT1Resm0tg4IbujK7q5euomn0dJ+Q016IVvz3r6pgFQDAx02K3DAkl/ycZRNID04zNn\nnH1d9z5tTe7LfXbOV78DSNltcu68G3Yc7zwRvrAHgLhzaP3nACcBgEkNyy9XBU4XBFB0jeaw\nX/QXwnXsEEJdqPrxEhkAAPXNr5uvFLteBQBAZX0sw9p1Wd4NiaDiykiWewNUpfjO0qxdaIQi\nJNdXb5ChwQB1WeHadgINS9nWbTyw6gWrTugpJ4fXPrzHI66sPchwgIIQGUDU/ODROeIAoL45\ngaFu2j91O09wiSrrGhnpqYpxA1l6/MH15gAAE31r2hIeS3Xr2DW73Im42tqndVWLw5apkgEo\nvZc/LmbooSJywwBuAJK8U1Dez8KGnSf6UoEkINtvkJFBH6na91ZETT3iyhhjaPG6sTW6/BMW\nAABA5uuh2n/gYOOBA3pL1i6QImrsGVPOdh2C9c4TmQ8W9a99CYFPWkPPQFdNon7nic2sdp5g\nMZAAJyoA6O1u8e+CBU4TuyIfK24AmXn/K6k/L1Nil3neWhBAYJpfZXMdIFQPEzuEUBcKnCkO\nACS93R9bqpW8fQAAgNziMIbEqOC8dd0aaRobXzXftiIt5KTrVPP+ChJCVG5empSihu7QCS7b\nz95/k/PzS7LFBIUgiPL3tzbaGapI8HHzCIjLDxgxx+P+p0oi1LlJYkcQRE3Oi+NLrLTlRXh5\n+ERltYbP9Xz0tfqTlyEACM4MbFN4rGNqZYFiEF8UShAEQXwPnC4HADw6m5qsvlz1n+dgfgDo\nMfFKRpNLURh3YdWEgUqSgjxUQak+w2buuvepolH71q5b66Or/vriyn63OdaDtZRlxQV4uLj5\nReU1TWxXHnv89efw2alDsE7sCIIoTQn0dLbSU5IQ5OGmCvVQHTR+yaGQL42uRNcndkThbQcx\nAHKv8cdjCgimxK7qa7DbIGEA6LkolP31s9HfCxM7hBDqZPQHc8UAoP+2xhuh/X5azdUQWzhe\n7kR4vOfxKbJEmv/CQUrqJhMPRFQC/Hdt7YLJxiqqI3a/LCIpzj61bVhz62cjhBBC6Fcp8D/n\nlwcgNXSoeuuVUbfQhgWKe9pdfkKRnuZyPCL56e1kAIDEW56JAABksYGLztzYb9WxixoihBBC\nqBVpd7zu8U+YYaEiVHfLpuJz8G6n+dfzgFt7sYtJ+3YQRX+ONm0pxqM0+fCL0SvC/Pz+9zw+\nJSO/giIo2avf4FGTp4xQY731G0IIIYQ6UXHcmUVbVy8X7qmkoiwrQs9LSXjzubgGyNIjD19Z\n25fUegeoe2jbXrEAAAJKw2asGjajA2NBCCGEUNvIj3Xb+O3Wo6evU9PiPiVUcQtLaQyztnJY\ntmLmIKm2f9ejPw6J4HwbMoQ6hJ2d3fXr19PS0hQUWl9MHCGEEEKt6iaT7kTJp6f/7F851VJf\nQ0GMn4eP1lNjyBTXMxG5dOZ6FZetazcBVF72vPGK12EuEiQSafLNXxZ0x/o5tFoUHgExea1h\n9uvOR+d3Uupek3x72/Lpow01ekmL8lP5xeTUdcxnbP0nPo/1NjEItYpeQ3x6U/L8Ts6Dc98C\nT359eDEz5mFezhdc7xwhhNjV6u3ZF57jPZ5z3O3gtf5rjNoUUNt8PTPdZMUz4BFX09Ub2m9g\nZVZi5POb+57duhpw9untWUpN09fUE65HlzxfqfoLY/wlePpYzxoqC0BUFWd/jAl9/I/H41u3\no+9HHbXs+IcfqyLPbj4cKq2uqTZAbSCNUpKVFPP08pZQ31PjLz73c+iFD3QgzhTmVMUEfy8r\nbvjF4EdZTUZKeUZKuVQvXh0LUS6ebvKLKEIIdZ5WE7uvkXfu3OG82+ltiqbNeOTNlx/ftHCa\nRW8apbakJNF7qplL4N3Frv9MvDWVeRcScVXVmg8vdrjdmnVjkuivDbSz8RkvO3nSsu4DkRey\nYvCIQ0nH3U6vslyl1NHnoo45+alAupdww89Q5efrs03trvgv3/nQ/tQISkefEHVjhblVz+/k\n1FSzvr2clVbxIiB38DhJChf+woAQQi1p9TdgXecTjR12s5LnAqCI64yds3TdNq8DXtvWLZ0z\nVluMAsAlb+12+MQJZ91fEXyDHpO2HVgw4mdWBwCCfZ0PrNADKHv8OKpxbcFx2zYYcuffXLfz\nRVWbTkePWadCIvGPvVjQ6AARv06NROK3uZIPAACvNqqSSIIzA6u+3N8+zVhFQoDKJ6poMGVL\n0OfGs5U1mWH75gztIyXAyycqr2213Od1SZiLBImk6BrdpggBAIAkZr5yti4AERsVwzgnTc96\ncWrlpMFq0jReHl5aT42h0zfdesewS3R92GWJvq5j9RTE+HkFJNVNZ3qFfqth7l6OMasDAB4F\n23k2EgC57983vjIINY9eQ8T873tzWV2twpyq/yJ+yYblCHWisjd++92XzLA21uwpyEUikbjs\n2Xz8583GPiQWpBc/7dyA0Z+n1Tt2ysNdXIYzFny7OlEnqEBn5Z1r28YqCzAeOfTBf4P9jMPn\nQh1ilyh3dKBtQKPRAIBKpTY91HuJl/OxIUePup5c/GyJIsc9k/VcnA32rg3yvvTFcYl8Q3lV\nqPf59yDu5DyZ4UYg8cV3isHNl7IjLW1n82a/DPC/udUmtjAs4YAJf32V7wHzjSec+8itaDZ1\nsbEsOeOl3xLjGHP9DnhWrfbdGC7uhj2ga96dnmDuEpAjrjPGesb4HtSi1JeBN7ZP9r+3+VH4\nlkENf6FEirfN4H8/6trbLhpDynjp53th9fCwhJsvL4yXav50BY9vPcoFkB0wQLz9saO/xpek\nMsYZ2OZ8TixV1RHkFcB7wejPlR24a9WOGOASltOQlchKzuKsNVnZYoaJHGMJzbCFf5HRX4rD\nnSoq78+RBC7jI5+bOZ52aDAFJOc+6Pq9YukpnobcAD2cHzLsb1Z+yQoAeq2KIogc34nCABJT\nbxXUHavdeq9h39uW5fhYUQE0mfaOLrluKwwgv/J5dV1B3AYVAABew40R+XW7RNdkXJpAA6Da\nXCiqb1bxr4sUANeAtVEl9UVl8Zv1eaA+VLbUDo025yHDJfj+aKkaBYBn2Mlv9UWJu7W5QXLk\nkbcMuymXxXsaCwK5/7b/mMKmDFgb8TOi0tjNOtwAEo5BpY1O/Pb8Mmdn53lO9uNMVIXJAIL9\nlzzIZitk3FIM1XpxNyfgRDo7f1ITSlrvDqHfV3FiaHDU+5wKet1OoBQ7Nr9zEjaoA1AdAlqv\nif52nD6MHPPgQQ70t7KSb+a4grVVf8h58CC2bWlmhymL2mq/OaKqx8SDWyxZ728mYb/HTZ87\n99q6PdFtmY+VsFswRQzenjn17OeNhuyr3v5F0G/ufCPmOwoK8/dvHiRS92gQWdrBZSINfkRG\nxtcdrgm+eCULROy3btT/eb+Mr//aHY6SbQir/NkhFxcXFxeXOdMnmPVVtjycTJcc6XV4lkzd\n8fDjh19VKTutt+9RmvtTac8Zsy2o9Nd376UxdCUyecvGhjt4/Dprt02TgNxr5wLKmU/5OfSM\nt7f36QvX7jz5UNZz1LaA4IMjmwnd19fXmUF0dDvmmVE3UpzH7v+D7NdE6LckqDFsuL6qBBUf\nFkWdhtNFC3NycgB6tLD2HUEQANnZ2e0Lq30q3hydZLU1iqy7zs9nqnRztUi9l3s5Hx929KCr\n98Kwxc1lqs3iG71wptLl/Ze873kYj+UHgA8+3iGVFDOXuY025CPrGOgyXmaSgoIcwPv8/LrP\nKXFxxQBmJiaCTN0PGaIHZx5wGlXlu0Dvdwznkhl3Ntxvlmp9/v7pxYsMAPAaKunFonFGRgZA\nr/pPOqamzBGZmOjDhQdxcW/BTp+hfNT5EuI8UVWc9fnt48vb1m6z0A73undnhS4/NPHs2bNT\np05xOibU7VVXsbskT3UlvfVKCHVX9JS7u9bcS8mt5pNU6j/EZvKYfmL4ZAJqjNPETkpKCuD1\n3TupbiuUWPzGQXz0v5MAICcj0/TYL1Iau2/cCNdHP/TWBD3cbdziIh+8QzfvHHvR8e7WjQGO\nF2w4PRHZaIGz9oF1N7z/OTh2lhgRe+p0NCEw3nl6z0b1+EREmJ/y4+LiAqipqb/TV1RUBMAl\nJdVoh10BKSkB4BhtzsOCM5ZAVJVkJz05t2bOhjsu1it7vTxoXvte8Pfv3wFA3/Xu7pF8TRtT\nFTQYomwSEU1KigpQWFjI4rwkbiFpFUO7zXe0SPpam1fP2jcq3l2jSa21a9fOnj3750c3N7eH\nDx9yPkjU3VD5KWVF1WzW7Oxg0F8iNhZ27uyw3tzdQVu7w3prVlXE6Q0R9R88N6zSmnPK7+TU\n3ritBGLE6c+D/sSJCgcOvdw4YYH05T12WiIMU7n0/ISrax3co2qg18QJv/it2HqFz7aMsdr6\nHIzcg+9vM6K1Wl9iuofbgSC3y2v3rBgzguOzqc5eYLnZ+YH3xbRZC5O9z6eA5BznCRyvFycs\nLAyQlpWVB8CYSZVmZZUCSHAcFAAAkLgFpbRGu/kHlOoM2nnIafXYpFPm/FD/Pkk2WdrS0qCV\nLqqbRFSYlfUDQI7W0mXl1rQcKrP59euwp/nuGk2WklFQUGDcZEJUtJstNoPaSLwnD5uJnbgs\ni3ehEGqD/FxISWj4WFkF39I5aN5TDngaXkqD/NwOC6wZND2nHRcMrE20FGVo9OyPcQ9ObnI/\n/uzsjFHCcm/3m/B29unRH4TTxI48xP3k7Ltjz8V7T+vvu9V8zJC+igpS/GVZnz+9fRIUmlxM\nALfKPG93465YSDT34coR4w/E8Q3bHRywTlew9QYAQOqzfO/c45YnD64+01eF4zNKOiycvPrh\nlVNnnkn/55sDimucR7B+oK8lKtraQpDw6unTkvljG4KuePo0huOuGuPR23h43kXLk2ddDyyP\n2dCXBCqGhpIQ/9nv2vPtBoNbCTUuPLxk4fiGiMqfPIkB4NHR0WypVXFKSjYAcHPjr5CIbQp9\nBL4wLrjTDD4hiqQcJnaoY/DzwTznho/ZmcTpoxw0t50CklIN01b8nZ5ZyU9w2/Dzg4Km+fwj\nxjq0QYN3xh/d7bvZZHbr9zHQX4Pzr1/x0afCA6Vnzd37b3rSo3+SHjEe45Yfse6sz5bhv/5G\nDP2bv4ul/el3IiMP/Xt76f/Zu/O4mtI/DuDfc6vbqpskkbKUYpSpZBiVJU0m689azWAoo4y1\nZIlQyRAhxhghg7FrQbZhpBApSsagiLKXULQv9/7+SLml7dZNOffzft0/5p5znuWe6eV+7nOe\n8xyDKq4zVkdukNfKIfsmnVrulVIgcrOKw6dPar9v8zZbt7fZjMniab3qEWilBk/6Qf2vgAOe\nq+ZarfwwMy3/9tple16JXtcn5AZ5LBmwyzlirceR6SHjVRnLmbMNA5f++5vTwqHh6y1bl/+z\nJMh+cPrks562/T/eOZ8Z5Olz7bvVH+6fyI33Xbb/FalNnDL8w8l9HR18Sb7fsK9bl/8NlbyO\n3zp10akS4vYbatVCDL0HCdFSg6upp/AsqZZs170vjyOFOecgHvm55OdZYXKnrCjfh7v/IKKP\nxXeFfP6/TNlejj/2WJkQFxMTTw4DPnvz0GzVZ1xFqv3gleeSZ8WeCD518ca9Jxnvi2RaqGl1\n7dlv6Njhpm1kaq9A/O6vGzVu+91ijmYX1Ti/6ZMr7DN0CJjXr6af+eoT1izY8PfS+Af1aFjK\n7JdpX29elvCMZL5zchB9zI+ISNZqxbaf/h6z+1dzg2v2Y/pqMi9iQg9EaVgPUDkRweE0dOxT\n02GFk6/FxtClvjGjfb+RNnAPCogf5BTib9XljPVIa2MtpZKsp/diI8JjHndcdlco2CmY26hu\nHWAQYzfGTIt5ER2y/9xDvvakbWuGlN0U8TZi1Sh3e9XOX+l30mrXUurdy5T/biQ8zyNO2yGb\nA6a3r6Y7AFXq0U8lP7vk9fNqf1117a2s0UmEX2wANeNwREtytdbWBFRUVIiooED0QQlgs3r/\nXXM1eo2e0Wu0OPvSAFmvXxcTEf/Z5QO7Ky/DPdh8c83BjpjurmunbLXa8aw+TXdzmNJn2dzo\nFiOdfqj3OpGtRwZeOdt9sef2kwc3Rcm01jMbsynKk7dC/QR1UG7wM15lzN2XWm93OPvb4l1z\n/pnaTkrPISjB5ID/+j+PRZzYceG9QFGtbbuORhO9PG0nCj91jNFxCguwX7bI7/Dmg2kFih16\nTlrjtcrV8uNNxu1GLl2TEXQu4trdhMgbb/OllFppGdo4Dpkwc7a9UUsMq4BopKSZPsNaJd14\n/zAhu6RIQEJ/QQotpL4yU9HoiFlEIE4chmTEdytOk/yT9y4yMp6IdHTqN6YAbMUIali6BOog\n/7Sj5pCdXOd/nvwxSIzzygQJS7sa+Ty2C3p/YMznnq5200PXeOXLn8Kydw1r1HZsbW0PHz6c\nmpoqfEcFSLjCfH5aav6710XFhXxZBalWbbmtNGU5HPxUADG7/I9g1o9i+/r7/QDT11LEv9IT\nk+WG7y62PVJ8cOwn+15F7doXm6nc6wcHM3UioszYYxdl+w7pUT71hZ9x/Q/HkTOPP5fp43fn\n6jzdhn4AYBFMcW+gpzvW7H9D3TxnWDbkVGZnZMioqX0cVsxN3Dh/UxIpjRv1Hf4PgUThynG0\n9KtYBBFAvBjxjtjVOdQ9DnFfdvwFEdHTy0VEgmu/T558gohIzcbTz7bjh6Oehfm4+CZ3WGhe\nFuwiV42cH9dKx6Brp/ZtlUvSH92Ou/k4WyClOeL3PbOR6qCCusSG+G3OASI+ScLEaes043p1\nqFkozn6VkV39oyullNRaM7f2/3Ym6UX0we0R+Wq23rMNGjSicN3TaEyE4bABhp00FHOfJ0Wf\nCr6UWqBms813nHId+6OEAAgAUGcchqTFNzGu7sHuTVzo7t2JH9+nROxOISKiDmozPwa7ytQG\nzXD/OfRy9M0HcUkx74plVdrqWk0cPmmuy48mmPkCldQlDiSfDQgIFq3aMVZfdLC76dOrl29q\ntbs7LIxNmRu9zX3JRVmV9l/br/PfMraB9wF3/t7BJinsYtC14Lfvi6SV2+kPnDbTZckca22m\nrv1ZbVrtbgAAqIRhSFpKbJdimTrPsjPyuSfwqf2o1Q8Eq4XeKxlP/HXbxHp1DSROXYJdW9Oh\nQ/NFq9a06Z48IQ76U/eds8qrdrd8R33SMI0QzBRbg9rDvPcO825If8TJyOdBHf7hAQD4cjFE\nUk0xYgfQ2OoS7MwWnTjR6B1pVlromlk1p1kLza0/AABfOgbBDtgJM7MAAEDicBiS/sKXOwGo\nEoIdAABIIg4jvjl2SHbQbCDYAQCAxGHEeikWoPlAsAMAAInDEEk1xTp2AI0NwQ4AACQOw4j1\nUqy4KgJoMIxEAwCAJOJwxPaqc7LLvR2yfumsicPMurdTkmYYRtouqO4dzk8+5vVjP30NZTm5\nFupd+tp6HErMrdcnB1bDiB0AAEgc8c6xq/Ol2PQTv87zuUHSyu27aaqlJaXVvYnC2/6DLVwu\nZrU0HDbeqbP0k0shwSvtTp+/HxnuYSxfr04DS2HEDgAAJA7DiHPErs6XYtVG+p2Nvf8qO/PJ\nrXXfy4jQ3+SNjgsvZrYauTMu/viOjf5bQ2JvHbDXfB/t6bDuP7FdUQZWQLADAAAJJOAwYnsR\n1TFcKXUb8J2prpqsqJPy4gL/iCkkIxe/yR0/3PLB0Ri3dpEZp+RmwLZoJDsQgmAHAAASh2FI\nSkpsr8a+KzYlPPwRURcbmwrPINK0selB9DQ8PKlxW4cvC4IdAABIHIaIw4jt1djBLjExkYj0\n9Ss9F7yTnp4MUVISgh0Iwc0TAAAgeRjicL6YS5hZWe+IpHg8xYqbOSoqLYjeZGbmEeEGCvgA\nwQ4AACSOvAJNXvTxG/DtK0HYnyV1Lz7CQUpF7eMwnZyCOPtWdwKBgIgYrI8MQhDsAABA4uTn\n0t61xcJbOKKkoxMVU+AcP1HucBUdj6dMlJmVlUMkPGjHz8rKJuLyeHKN2jp8WTDHDgAAJA4j\nvgl2IiXC+imdXVc6005Iyv37RUR6enqN3gH4giDYAQCA5GGIIyUQ16uxr4V2tLTsRHT/zJmH\nwlufnz6dQKRpaYlgB0IQ7AAAQOKI965YcXsVtcvf339nVHrZBhPH6d/IUPwGtz2PP1wD5qcF\nL1h9mS9l5PxzH0yxAyGYYwcAAJJInMNsda7qcYj7suMviIieXi4iElz7ffLkE0REajaefrYd\nPxz1LMzHxTe5w0JzBzP10i06cwJ9w8xdQ6cYmYSMHdiJ8+RS6LEb6Uq9vQPnGSDXgTAEOwAA\nkDgMIxDjcidMXZ88QW/iQnfvFpoqlxKxO4WIiDqozfwY7KrANXD5+0Zn36V++//Z/8dpUm5v\nOHrxRu/Fdl2xzglUhGAHAAAShyHiiG8uUt0H/4x87gl8aj9q9QPB6k+2yuuM9Nw/0lOknoHk\nQbADAADJ0/iPiwBoEgh2AAAgcRgiKTFeikVGhGYDwQ4AACQR0hiwEoIdAABIHIYR6xw7sdUE\n0FAIdgAAIHkYYsS4kCuSHTQbCHYAACCJOIzY5tgBNB8IdgAAIHHEfCkWI3bQbOCRYgAAIIkY\nRmwvkeQnH/P6sZ++hrKcXAv1Ln1tPQ4l5tZa6LZHV6YKGjMv1/PTA2thxA4AACQOQ8Q0xXIn\nhbf9B1u4XMxqaThsvFNn6SeXQoJX2p0+fz8y3MO41mdIcDoPmmjRXngLr0+b+vQX2AzBDgAA\nJI9YL8XWWfJGx4UXM1uN/PN68OSOUkTE9zwywXT8AU+HdaPiPLrXkg9lvp27a9ewz9JR+HLh\nUiwAAEgicV6KreOIXVzgHzGFZOTiV5rqiIijMW7tIjNOyc2AbdG4lwPEASN2AAAgcRhGIMa7\nYhmqU1Up4eGPiLrY2OgKb9W0selBUTfDw5PoW/0ay/OTj/+64GRyRrF86049zIePHWKoKtWA\nXgM7IdgBAIAkEuc6dnWTmJhIRPr6leJbJz09GbqZlJREVHOwK4reviS67M2aJfMMHLeFbLXv\ngi9yEIZLsQAAIHEYIg4jtlcdb57IynpHJMXjKVbczFFRaUFUmJmZV31RXs+ffHafu/nwRWZe\n7pvU2+cDZpqp594OnPj9gkv5DTgNwEII+gAAIHG48oyNo1z52/dv+VFHC+te3HwUV0nl48gI\nV65BC9kJBAIiYmqKh1qj3JeUv9HubjntNzNjXu++KxM2r9q/3MKB15DmgV0Q7AAAQOIU5gv+\n3lVhhEyk5eiijhYIvx3nplCXUjyeMlFmVlYOkfCgHT8rK5uIy+PJVVuyCrK9HH/ssTIhLiYm\nnhwGiFIS2A2XYgEAQOKUPnlCXK86ZsLS2XWlM+2EpNy/X0Skp6cn4mdQUVEhooKCglqPBEmC\nYAcAAJLo8z95oqOlZSei+2fOPBTe+vz06QQiTUtLEYPdu8jIeCLS0dERrRywHIIdAABIHIYh\nhiMQ26uO2c7Ecfo3MhS/wW3P45LSLfy04AWrL/OljJx/7vOxkldRu/z9/XdGpX94nxl77Pit\nV8UfK+JnXP994ox9b0mmz0S7CoungMTDHDsAAJBEoj7jVRx05gT6hpm7hk4xMgkZO7AT58ml\n0GM30pV6ewfOMxDqzrMwHxff5A4LzR3M1ImIMiNXjZwf10rHoGun9m2VS9If3Y67+ThbIKU5\n4vc9s5HroAIEOwAAkEQcMQa7OlfFNXD5+0Zn36V++//Z/8dpUm5vOHrxRu/Fdl1rfFCs2qAZ\n7j+HXo6++SAuKeZdsaxKW12ricMnzXX50aRlE8RTaNaY0rusAT4/W1vbw4cPp6amamtrN3Vf\nAECypNwuOrY5R1y1/W+WYofuMuKqDaAhMGIHAACSSJxPnsCwGTQbLLl5QpCdcvnQeld7K9Nu\n2qoKXHleu27m49x2RGfwKx6Xv3cYwzAMw3Sec6XyUpQRzmoMw4wN+mydFq/yj1ZKiquoqmUw\nwG7RrutvG2dMtq7nHACgGRLfLbFNMVcPoFosGbF7tmOChUsUcVvpmfTsb/hNYdqdmCtB66KC\nD4QFXg6d0unT+ProD7fNs664sm7OKbfrsCn9NYkERe/TH964EHnINzI49Prp2M1WyuJuSuRz\nDgDQbDBEHI7YfvUi2kHzwZKvX66W5dwtfyelpyVe/Tv0cNDJyDuPErYOUxc8Pz7T7VBW5aNb\n6eqqFF31cQ9+2xR9bVTyZnO2bt26dWtA4L7QC3cf/jNHX6o4aYv79kfib0q0cw4A0KyId8QO\nyQ6aDZYEO/Ux3humW3fhSZVvUfrKaYNLT6LcyMjYykcrjfRe0kfmbdCilVeL6tUc/8YiHYZR\nGLEns9IOQcIiPYZRGL6vNDLe9NBlGKXJJ4qenF7xg5mOmqKsfMuOvcZ5nipbwahcycuIdY79\nu7ZRlJNvqWU0dO6ft7IjnNUYpqPb9Xr1kIiIGFVLVwcTIkFc7A3h66P8tKvbXMf01dPgyXHl\neO269Z+wLPhe7sf9Zd3OvbPfbURPbVUFOcXW+v0mLjbV5gAAIABJREFU+114Ltxt0c45AEBz\nwhAxHLG9AJoPNv898ng8IpKVlf10V5dZfk4d6cFmt60p9amZ09PZqRcn71TAX08qbC+6ELDr\nPrUa7zS25ceNgif7x/UauSVRte94h0lDu+THB3kNH+h2SShI0euwaWZWbjtjCrrbznSbaW9a\ndGKWmc36xMrprx5Kb3qWlvl4t1bJve3/MzZ3+u1SfrchE2e7zrC3aJV8ZMVYUwvPaxVuEBMk\nBwzv6xic3WP8jHmz7I2Lr++e/11fh6NpNbdXwzkHAGhGGGIYgfheTf1xAMqwZI5dFQQPd+25\nRKQ+fHjvKvbKmi3/dfSeH0K8F4dM2j+aJ3LtHR1+sVk25WRA4L+zPA3LNuYcDdiXRlquTjbC\nuSY3PDTN49Jd794qDBHxX+4d23Vi6B9rg7wtJrUgIqKC8x4/73zIfL3wUtRq09IHQ3vN9uzX\nyyuTSPSeCRG8CV+/M56I29f8mw8JXnB3rf2MsOLvfksInflV2bJJebfWfme2YMW09XYJS7uW\nd/vy6dcLo26v7v2hRzM8zXt77fl5gZ31bpvqnnZd8zkniouLS05OLn/75MmTKg8DyM3Nfffu\nnZqamrQ0e/+NgqaGNAasxNYRu9xYL7vl0UXqo/09rbhVHqFmt9rdVCbj4KLV1+tzPVbNdvo4\nVfpvx7ao8nG19AMBR9+R4dRp30pVOFR72vrlpamOiDgaPzqP5lFBTEzCh90lZ/fsSyMVOy+P\nD6mOiOR7LPSZ1Loe3cqL2ujs7Ozs7Ow4YdTArzpbbUritx7st2lK2w/7L27ZdLOo80+L7dRz\nMsrltJvoMEiWf+v4yVShqlTGenr0Lu+RgvFC7x/UKOPgzrC8atqu/ZwHBgaOF3L16tV6fESQ\nBOnp6RkZGVlZmKwJjYUh4nDE9gJoPlj595h/e/OYoV6xHJNFIX/aa1R3FNNlrp+TluC+v1tA\nfQaO5G1+mdyJnv0VcPLDRdUHfwaEF0oNdJ6qX/FAjnEvE+FBB0Zbuz3R27dld24kx8e/JzK2\nsFCqUL25ec969Krw3omAgICAgICd+45G3MuitiMDr5yaZViWs1KuXn1B9NCvf+uK2joeKyB6\n8eKFUFXG/fpV7JGFhSlRYXz8f1U1XKdzbm9vHyDE1NS0Hh8RJIGamlrLli1Lr+wDNApxXocV\n7VJsfvIxrx/76Wsoy8m1UO/S19bjUGJu7aUaUhAkCvsuc+TErRtp7Xa+oOeCU+dWmdW4yIdc\n/+UrR+yZdNzLI2zS7uGiNsT5drqT0YZFRwIO+Y+YoiqI27b9ukDxf04T2lU6Tl5FpeKMM2lp\naaKSkrKRvnfv3hFJt2mjWrGYYps2iiQynuO5zB1WJCjKTk+8tHOB45JjzsNcO1zztyz9gnz9\n+jURmbodXzW4isfXyGp3E+rlJz3itWkjS1TVIEpdz7m5ubm5uXn52/Pnz1+/3oCbQ4C9lJSU\nlJSUaj8OoAGa5KaHwtv+gy1cLma1NBw23qmz9JNLIcEr7U6fvx8Z7mFc41PF6l0QJA3Lgl1W\nlOeQoV5X6NulZ097f1v7r321Cb7uG06571242mWItcit6TpMt1rudCZgT+qUX5ICdiVTa0en\nUSKvF6esrEyUmpb2hkg4SeWkpeUQqYncKSIiYmSU2hjYuB8NyzHuvXLjT/NHJG6zVKCyexvS\nORpWVr1qqaL4kx5lpaUVELWvPIgi6jkHAGh6Yl5YuK5VJW90XHgxs9XIP68HT+4oRUR8zyMT\nTMcf8HRYNyrOo3v11dS7IEgcNl2KzTjnOtDa64r0gFXhZ+uaMJiuc9dO1eLf9Z+/46noLbb+\n8Zexyvxr23ZEhQTsf0UdpzhZVz25rCY6RkYtiG5evpwtvDX/8uUboneoEm5Pj00/a9HTQLcN\ndwRERDp9+rQmehxy8JPnbnwq/uLFCj3Ku3TpBhHX2Li70Mb6nHMAgOaA4QjE9qK6rXUcF/hH\nTCEZufiVhjMi4miMW7vIjFNyM2BbdA111LsgSB62BDv+86PT+g3fcLPF4I0RpxaZiHANR26Q\n18ohLfL+We51vkDkZhWHT5/Unu5us3U7ns2YTJvWqx7nU2rwpB/U6e0Bz1Vx5bMl8m+vXbbn\nleh1fUJukMeSAXL8+LUeR94QEWM5c7ahND34zWlh+CvhfwoE2Q9OHYqssJZJZpCnz8cVUHLj\nfZftf0VqtlOGlw361/+cAwA0vc//SLGU8PBHRF1sbCo89UjTxqYH0dPw8CTxFwQJxJJLsffX\njRq3/W4xR7OLapzf9MkV9hk6BMzrV9O6auoT1izY8PfS+Af1aFjK7JdpX29elvCMZL5zctCp\nRw1EslYrtv3095jdv5obXLMf01eTeRETeiBKw3qAyokIToNvt9J0WOHka7ExdKlvzGjfb6QN\n3IMC4gc5hfhbdTljPdLaWEupJOvpvdiI8JjHHZfdte3fpqycgrmN6tYBBjF2Y8y0mBfRIfvP\nPeRrT9q2ZkjZWic1n/Nd8/o1sOMAAI2IEescu7plu8TERCLS1690i10nPT0ZupmUlESkX2W5\n+hcECcSSYJf1+nUxEfGfXT6w+3KlfYPNN9cc7Ijp7rp2ylarHc/q03Q3hyl9ls2NbjHS6Yc2\ntR9dtdYjA6+c7b7Yc/vJg5uiZFrrmY3ZFOXJW6F+gjooN/gZrzLm7kuttzuc/W3xrjn/TG0n\npecQlGBywH/9n8ciTuy48F6gqNa2XUejiV6ethM7CRVjdJzCAuyXLfI7vPlgWoFih56T1nit\ncrX8eMNrzeccwQ4AmjOuLPPtyI8XGnLfldyKEOEW068HKsi3+LiylQy3TskuK+sdkRSPV+nO\nOI6KSguiN5mZeURV3wdR74IggVgS7ExXPxCsrsNxchNOCCZUsV1h0Pangu31ajr/1q0kIo0f\nnUd+ei3SyOeBwOeTrboeNwUelbZJtbWc/6fl/I8bBAlLbxWTXLduHevYj+o+GhG1mfJ3zhSh\n94yq0Q/ee37wrq1Kxa9+WHf8h3XV7K3rOQcAaH6KCgXXwt4LbxHpXopKKXDQxIatJi8QEBEj\n+t0c9S4ILMaWOXZN5umONfvfUDfnGZYNycjZGRkVJvjlJm6cvymJlIaP+o4l0RsAoDlpkgWK\neTxlopKsrJyKm/lZWdlEXB5PTuwFQQIhNlSlOPtVRnb1T2qVUlJrzdza/9uZpBfRB7dH5KvZ\nes82aNAPpuueRmMiDIcNMOykoZj7PCn6VPCl1AI1m22+45Tr2B8l/J8EABAJ87nvJtXX1ye6\nlpiYSGQitDnl/v0iIgM9PfEXBAmEOFCVmz69evmmVru7w8LYlLnR29yXXJRVaf+1/Tr/LWNb\nNqzBzt872CSFXQy6Fvz2fZG0cjv9gdNmuiyZY63N1LU/q/EQBwCAuhPrOnZ1rKqjpWUnunb/\nzJmHv5p0Lt/6/PTpBCJNS8vq81m9C4IEYkqv0EMF7x9EXUup7pGoRPIde5vptpDg/oiJra3t\n4cOHU1NTtbW1m7ovACBZnj8ouHgoU1y19bdr2VanLsuYJq/t3W1BDG/U7htHJmlLERE/LXiS\n6dh9L4xW3IzzKL/08ypq177YTOVePziYqYtUEAAjdlVqoWtmpVv7YZ9Nc+sPAMCXjhHrJPO6\nBiudOYG+YeauoVOMTELGDuzEeXIp9NiNdKXe3oHzhMPZszAfF9/kDgvNy4NdHQsC4OYJAACQ\nPExTLFBMRFwDl79vHF1u2z3vyv4/tuy9+Lbz6MUHYs8vNaltuZJ6FwRJg0ux0GRwKRYAmsqL\nhwWXg96KqzaLcS01OtW4XirA54JLsQAAIJFwCRPYCMEOAAAkDiPiisQAXwoEOwAAkDwMMRyx\nzURCRoTmA8EOAAAkEdIYsBKCHQAASCIEO2AlBDsAAJA4DCMQ46VY3IcBzQeCHQAASCJxPlJM\nbDUBNBQWKAYAAMnDEMMR26vhyS4/+ZjXj/30NZTl5Fqod+lr63EoMbfWQrc9ujJV0Jh5uaHd\ngS8YRuwAAEDiMEQMI8b1+RtUVeFt/8EWLhezWhoOG+/UWfrJpZDglXanz9+PDPcwrvXBEpzO\ngyZatBfewuvTpiG9gS8cgh0AAEgehhjxXbJq2FXd5I2OCy9mthr55/XgyR2liIjveWSC6fgD\nng7rRsV5dK+lbplv5+7aNawh7QO74FIsAABIIoYjENerQf2IC/wjppCMXPxKUx0RcTTGrV1k\nxim5GbAtGk/9BBFhxA4AACQOwzSX5U5SwsMfEXWxsdEV3qppY9ODom6GhyfRt/o1lucnH/91\nwcnkjGL51p16mA8fO8RQVapROwzNHIIdAABIInEGuwZUlZiYSET6+pXiWyc9PRm6mZSURFRz\nsCuK3r4kuuzNmiXzDBy3hWy174Jvd4mF//UAACBxpGQY/W+Uy98W5vFT/ntf9+Idu7fgyn+c\nyyQtXf9kl5X1jkiKx1OsuJmjotKC6E1mZh5RdTdQ8Hr+5LO71zALg45tefz0h/Fnti5buiUq\ncOL3yu3/W28hV+8uwRcNwQ4AACROSYng0b8fk5xAINqo29P7OcIDfsoDubWX4cdtn70zQbiQ\n669jOld7uEAgICKmpnFFrVHuS8rfaHe3nPabmTGvd9+VCZtX7V9u4cCrvU/AQgh2AAAgeQRU\nXMQX3iDSldmS4gpl67TaCT/p5O+/H/v4vo203a9jOhOPp0yUmZWVQyQ8aMfPysom4vJ4Ig28\nyfZy/LHHyoS4mJh4chggSklgDQQ7AACQOGJ+pFhdSNsdFdh9ullfX5/oWmJiIpGJ0OaU+/eL\niAz09ERsRUVFhYgKCgoa0FP4omG5EwAAkESlN8aK61VvHS0tOxHdP3PmofDW56dPJxBpWlqK\nGOzeRUbGE5GOjk79ewRfNgQ7AACQPOJ9pFhDmDhO/0aG4je47XlcUrqFnxa8YPVlvpSR8899\nPkbGV1G7/P39d0alf3ifGXvs+K1XxR8r4mdc/33ijH1vSabPRLsKi6eAJMGlWAAAkDhifqRY\ng6rSmRPoG2buGjrFyCRk7MBOnCeXQo/dSFfq7R04z0BoKPBZmI+Lb3KHheYOZupERJmRq0bO\nj2ulY9C1U/u2yiXpj27H3XycLZDSHPH7ntnIdZILwQ4AACRSs7lkxTVw+ftGZ9+lfvv/2f/H\naVJubzh68UbvxXZda3xQrNqgGe4/h16OvvkgLinmXbGsSltdq4nDJ811+dGkZfNYexmaBFN6\nQzXA52dra3v48OHU1FRtbe2m7gsASJbXL/ISLqaJq7av+7Vp1bbGFAbwuWDEDgAAJFFD58YJ\nV4URMmg2EOwAAEDyNJtnxQKIF4IdAABIHIYEYr15Qmw1ATQQgh0AAEgiMV6KBWg+EOwAAEDy\nMA1co6QS3IYIzQWCHQAASCIxzrHDdD1oPhDsAABA4jAMfe5nxQJ8FphiAAAAkkicjxRr0Ihd\n7u2Q9UtnTRxm1r2dkjTDMNJ2QXUvnJ98zOvHfvoaynJyLdS79LX1OJSY25DOwBcPI3YAACB5\nmOZzK2v6iV/n+dwgaeX23TTV0pJEWDa58Lb/YAuXi1ktDYeNd+os/eRSSPBKu9Pn70eGexhj\nvWRJhRE7AACQRAxHILZXgzKi2ki/s7H3X2VnPrm17nsZEQomb3RceDGz1cidcfHHd2z03xoS\ne+uAveb7aE+Hdf/hMrPEQrADAABJxDBiezWMUrcB35nqqsmKWk9c4B8xhWTk4je5o1TpFo7G\nuLWLzDglNwO2RSPZSSoEOwAAkDgMI77hOo6gSa7qpoSHPyLqYmOjK7xV08amB9HT8PCkJugS\nNAcIdgAAIJEY8b2aQmJiIhHp6+tX3NxJT0+GKCkJwU5S4eYJAACQOBwppk17Xvnb4qKSN+nZ\ndS+uqq4kLSP1sTZOE4S7rKx3RFI8nmLFzRwVlRZEbzIz84hwA4UkQrADAACJIxBQQX5h+Vt+\nCV+kZe2KiopKSkqE66u9DD9u++ydCR/fKw90/XVM57q3WVcCgYCIGCyaLKkQ7AAAQPIIBO8z\nKyz4JlIQynmXX6Ey7Za1l+Ennfz992Mf37eRtmtQsOPxlIkys7JyiIQH7fhZWdlEXB5Prv5V\nw5cMwQ4AACSPmJ8VWwfSdkcFdmKsT19fn+haYmIikYnQ5pT794uIDPT0xNgUfElw8wQAAEii\nZvPkiXrqaGnZiej+mTMPhbc+P306gUjT0hLBTlKxJNgJslMuH1rvam9l2k1bVYErz2vXzXyc\n247oDH7F4/L3DmMYhmGYznOuFFaqI8JZjWGYsSI8yaVZKf9opaS4iqpaBgPsFu26/raxfpQ2\n6DE4AABNiRFnsPssue5V1C5/f/+dUellG0wcp38jQ/Eb3PY8/jDdj58WvGD1Zb6UkfPPfTDF\nTlKx5FLssx0TLFyiiNtKz6Rnf8NvCtPuxFwJWhcVfCAs8HLolE6fxtdHf7htnnXFVbeKur5o\n3K7DpvTXJBIUvU9/eONC5CHfyODQ66djN1spi7+x+j8GBwCgqQnEeSm2YSnqcYj7suMviIie\nXi4iElz7ffLkE0REajaefrYdPxz1LMzHxTe5w0JzBzP10i06cwJ9w8xdQ6cYmYSMHdiJ8+RS\n6LEb6Uq9vQPnGSDXSSyWBDuuluXcLct++WFQF96H+8+z7wTYD3Q+cXym26HRwfa8Cke30tUt\neXDVxz14ypExdZjw+iWRN5uzdavVhzeCN+Eufa03Jm5x3z7Pal4nsTemNtLvrFV7Y0MdNdmT\nk+WG7y4WewsAAI2EIabZXLJ6Exe6e3fix/cpEbtTiIiog9rMj8GuClwDl79vdPZd6rf/n/1/\nnCbl9oajF2/0XmzXFeucSLBm83fdMOpjvDdMty5PdUSk9JXTBpeeRLmRkbGVj1Ya6b2kj8zb\noEUrrxbVqzn+jUU6DKMwYk9mpR2ChEV6DKMwfN9bIiK66aHLMEqTTxQ9Ob3iBzMdNUVZ+ZYd\ne43zPPW4pFLBkpcR6xz7d22jKCffUsto6Nw/b2VHOKsxTEe36/XqIRERMaqWrg4mRIK42BvC\n16T5aVe3uY7pq6fBk+PK8dp16z9hWfA9obvDyrqde2e/24ie2qoKcoqt9ftN9rvwvGK36/sY\nHACApsaUPnxCTK86LXdSPSOfe4IqpfiZCh21+oFAIEhZbVqhrLzOSM/9l5LSswsKsl8lXz28\n0q5rpYXtQMKwJNhVicfjEZGsrOynu7rM8nPqSA82u21NqU/NnJ7OTr04eacC/npSYXvRhYBd\n96nVeKexQgOBgif7x/UauSVRte94h0lDu+THB3kNH+h2Sfg2+9dh08ys3HbGFHS3nek20960\n6MQsM5v1iZXTXz2UrmckLfPxsdIl97b/z9jc6bdL+d2GTJztOsPeolXykRVjTS08r+VUKJkc\nMLyvY3B2j/Ez5s2yNy6+vnv+d30djuJ6K3wOWa9zXz7Oys+t3y8vgLoR45Mn8PsWmg2WXIqt\nguDhrj2XiNSHD+9dxV5Zs+W/jt7zQ4j34pBJ+0fzqjiiZh0dfrFZNuVkQOC/szwNyzbmHA3Y\nl0Zark42wlkyNzw0zePSXe/eKgwR8V/uHdt1Yugfa4O8LSa1ICKigvMeP+98yHy98FLUatPS\nX1pesz379fLKJBK9Z0IEb8LX74wn4vY1/+ZDghfcXWs/I6z4u98SQmd+VTZWn3dr7XdmC1ZM\nW2+XsLRrebcvn369MOr26t4fejTD07y3156fF9hZ77ZRqGeHMjIy3r17V/42JyenhoNBYj1P\nefs46TURcTiMQW8thRbcpu4RsBFDIq1IDPClYOuIXW6sl93y6CL10f6eVlV/K6jZrXY3lck4\nuGj19fqMCqjZTh+nSv/t2BZVPq6WfiDg6DsynDrtW6kKh2pPW7+8NNUREUfjR+fRPCqIiSlb\nf7zk7J59aaRi5+VhWj5+Lt9joc+k1vXoVl7URmdnZ2dnZ8cJowZ+1dlqUxK/9WC/TVPafth/\nccumm0Wdf1psp56TUS6n3USHQbL8W8dPpgpVpTLW06N3eY8UjBd6/6BGGQd3huXVo1+lli9f\nriPk5MmT9a4KWCzjxfvS/+DzBa/TRHjKE4BIGEacL4BmgpUjdvm3N48Z6hXLMVkU8qe9RnVH\nMV3m+jltGbDZ3y3gl4iZWqI2Im/zy+ROe9f/FXDS12yEAhE9+DMgvFBqoPPUSg9k5hj3MhE+\nzYy2dnui+2/ffnifHB//nmighYVSherNzXvSjjOi9qrw3omAe0JttR0ZeDFkim5Zfk+5evUF\nEfn1b+1XReEXL14QdSh7Z9yvX8UeWViY0u4z8fH/ka3pp4XrwtjYeNy4ceVvo6Ojnzx5UsPx\nIJm4stK57wvL/luq5oMB6g9pDNiIfcEuJ27dSGu38wU9F5w6t8qsxkU+5PovXzliz6TjXh5h\nk3YPF7UhzrfTnYw2LDoScMh/xBRVQdy27dcFiv9zmtCu0nHyKioVZ/lJS0sTfXzK4Lt374ik\n27RRrVhMsU2bekyA5Tmey9xhRYKi7PTESzsXOC455jzMtcM1f8vSa7qvX78mIlO346sGV3HP\nlKx2N6FeftIjXps2skRZWVmid+uDqVOnTp06tfytra0tgh18qoO+WnFRel5OYUt1RXXNRlio\nB6B0uA6XYoGNWBbssqI8hwz1ukLfLj172vvb2ieoqU3wdd9wyn3vwtUuQ6xFbk3XYbrVcqcz\nAXtSp/ySFLArmVo7Oo0S+WtIWVmZKDUt7Q2RcJLKSUvLIVITuVNERMTIKLUxsHE/GpZj3Hvl\nxp/mj0jcZqlAZfeTpHM0rKx61VJF8Sc9ykpLKyBqz2vQvD+AWskrcg16t2/qXgDbiXe5Ewz+\nQbPBpjl2GedcB1p7XZEesCr8bF1SHRER03Xu2qla/Lv+83c8Fb3F1j/+MlaZf23bjqiQgP2v\nqOMUJ2vRp3nrGBm1ILp5+XKFuUT5ly/fEL1DlXB7emz6WYueBrptuCMgItLp06c10eOQg588\nd+NT8RcvVuhR3qVLN4i4xsbdG9wvAIAmJyBGfC+AZoMtI3b850edrey231MZvPGf0NkGIqzN\nKDfIa+WQfZNOLfdKKRC5WcXh0ye137d5m63b22zGZPG0XvUIylKDJ/2g/lfAAc9Vc61WmpTe\ncJp/e+2yPa9Er+sTcoM8lgzY5Ryx1uPI9JDxqozlzNmGgUv//c1p4dDw9Zaty39kCrIfnD75\nrKdt/zblRTODPH2ufVd2V2xuvO+y/a9IbeKU4Vj4EgC+eIqKil26iO3hQ1wu7t2G5oIlwe7+\nulHjtt8t5mh2UY3zmz65wj5Dh4B5/apYy66c+oQ1Czb8vTT+QT0aljL7ZdrXm5clPCOZ75wc\ndOpRA5Gs1YptP/09Zvev5gbX7Mf01WRexIQeiNKwHqByIoLDaeiYqqbDCidfi42hS31jRvt+\nI23gHhQQP8gpxN+qyxnrkdbGWkolWU/vxUaExzzuuOyuULBTMLdR3TrAIMZujJkW8yI6ZP+5\nh3ztSdvWDBFa66SGx+Ds8rNtYMcBABoPh8ORk5Nr6l4ANIKqV7v+0sQurD5TDd7+vvy4vL+G\nElGHebGVyuf8M1Wz9OgxR0Rt+6l/HyJqMTbo/Se74pfoECn+FFZx6/0VXxNJ2YYKbyt+fn7N\nZIsurRW4cjzNHkNmBya8CRorTfT1ivt17EbpR+M5nvt018ud1gpE8oO2Pyt9z38dv2/pRKse\nWqoKXBn5lm07d/92hLP3zguP8it2O/u/fa7DjbVU5LjyrbqYT1pz/llx5c+nX/U57zCvLl0e\nP348EaWmptbxIwIAAEDNGIEAkwMaJP+0o+aQnVznf578MUiM45+ChKVdjXwe2wW9PzDmcw+r\n3vTQNV758qew7F3DGrUdW1vbw4cPp6amamtrN2pDAAAAEoJNN080iac71ux/Q92cZ1g2JH5l\nZ2RUmOCXm7hx/qYkUho+6juWXCwHAACAxofYUJXi7FcZ2dU/qVVKSa01c2v/b2eSXkQf3B6R\nr2brPdugQTe7X/c0GhNhOGyAYScNxdznSdGngi+lFqjZbPMdp1zH/ijh/yQAAIDEQxyoyk2f\nXr18U6vd3WFhbMrc6G3uSy7KqrT/2n6d/5axLRvWYOfvHWySwi4GXQt++75IWrmd/sBpM12W\nzLHWZuran9X1fBgEAAAAsAfm2FXl/YOoaynVPxJVvmNvM90WEtwfMcEcOwAAAPHCiF1VWuia\nWYltfSMxaG79AQAAgGYJN08AAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASC\nHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgB\nAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAA\nAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAA\nsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABL\nINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASCHQAAAABLINgBAAAAsASC\n3Wf31L8PwzD/21tcy3ERzmoM09Ht+mfpFAAAALAAm4OdIDvl8qH1rvZWpt20VRW48rx23czH\nue2IzuBXPC5/7zCGYRiG6TznSmGlOiKc1RiGGRv02Tpdb+WfopQUV1FVy2CA3aJd198KGqfF\nkqRQ77kTbPp066DRUkFWQbW9vrHlRK9DCW9KGqc9AAAAqIV0U3egET3bMcHCJYq4rfRMevY3\n/KYw7U7MlaB1UcEHwgIvh07p9GmmffSH2+ZZV1x1m6Cv4sLtOmxKf00iQdH79Ic3LkQe8o0M\nDr1+OnazlbLY2yqKCVy+6YKGfne9r/W+4UmoEfKxAAAgAElEQVRlpyXeuLzX88L+bf/bcyXk\nxw6M2BsECZGTVZT5qqCokC+vKK2qIScjy+bfnwAA4sXmYMfVspy7ZdkvPwzqwpMq3ZJ9J8B+\noPOJ4zPdDo0OtudVOLqVrm7Jg6s+7sFTjoxp2QS9FQ95szlbt1p9eCN4E+7S13pj4hb37fOs\n5nUSd1uyQ7amZGp0UP74N1T4+LBDP9t9R+euPGe3zVpK3A0C6xXklvx39U3Gs7zyLRwppuNX\nLXSMVBj8UgAAqAM2/xRWH+O9Ybp1eaojIqWvnDa49CTKjYyMrXy00kjvJX1k3gYtWnm1qEHN\nvr99cKmdRVcNZTmuvEp7w0GOq0+lFNRWiJ9+yf/ngd3aKMrJt9QyGuay+3Z2gzpBRESMqqWr\ngwmRIC72hvDlZ37a1W2uY/rqafDkuHK8dt36T1gWfC/34/6bHroMozT5RO6d/W4jemqrKsgp\nttbvN9nvwvOSitW3F051RMTVHv/zcDWijPv3MxvefZAwRQX82LNpwqmOiPglgof/vrsT/aap\negUA8GVhc7CrEo/HIyJZWdlPd3WZ5efUkR5sdtuaUu/q30cssOht7xOUpNRvwhy3meONSm7s\ndB/ac/D6f2tKi29OTTezdNkRnfeV7Uy3mXam+cenf2uz7p4Y5qoJBAIikpaRKd9Scm/7/4zN\nnX67lN9tyMTZrjPsLVolH1kx1tTC81pOhZLJAcP7OgZn9xg/Y94se+Pi67vnf9fX4Whajc1l\nRgafzyDS/PrrVg3vO0iYh/9m5b6r+p6iZ/ezM9Nr/XkEAACsvhRbBcHDXXsuEakPH967ir2y\nZst/Hb3nhxDvxSGT9o/mVXFELYoueUxcm5DbyeH0tR3ft2aIiFa5B4wwdT69YPJamxuLu1VZ\nqjBi2dRtD+jrhRejVvdSJCIirxke5r1XZhLVoxMfCd6Er98ZT8Tta/7NhwQvuLvWfkZY8Xe/\nJYTO/Er+w3F5t9Z+Z7ZgxbT1dglLu5YVzr18+vXCqNure5f1yNO8t9eenxfYWe+2URBu5c7u\nuZuu5vPzs9IfXr8Q9eCdUo9ZgUvMG9JvkEwvH+XWsPfFwxwV9Sp+jwEAgDCJGrHLjfWyWx5d\npD7a39OKW+URanar3U1lMg4uWn29Htdj+Wd37n5K8kOXrfqQ6ohIutO0da6GTEncjj/jqi5V\ncnbXXy9IxdbT40OqIyIF48U+E9RE7wHlRW10dnZ2dnZ2nDBq4FedrTYl8VsP9ts0pe2H/Re3\nbLpZ1PmnxXbqORnlctpNdBgky791/GSqUFUqYz09egv1aKH3D2qUcXBnWF7FJh9f2BEQELB9\n98Fjlx7ktvveO+ys/+DWVfdu/vz5qkKOHj1aj48IrFRcxC/Iq2mMOqeawTwAABAmOcEu//bm\nMUO9Yjkmi0L+tNeo7iimy1w/Jy3BfX+3gCciN5EcF5dF1H3gQPUKVXazHNiW6FF8fNXzzh7G\nx78jMu7XT0l4q0K/fj1F7gBR4b0TAQEBAQEBO/cdjbiXRW1HBl45NcuwLMamXL36guihX//W\nFbV1PFZA9OLFC6GqKvdI3sLClKgwPv6/ik1+vytbIOAXvnvx4OpBD8O73oOMBm+Iq3roRUFB\noaUQGaErxAAAANBwEhLscuLWDRsw60xezwWn/lllVuPKH3L9l68coZwf6eUR9k7EVrKysohI\nQ6NybGzbti0RZWZmVV9Kuk0b1YqblTQ0FKs8vkY8x3MCgUDAL3z/8t9Tv9povDzmPMw1vLzh\n169fE5Gp2/FzVTkwTeha8ac94rVpI1v2IStjZFpo6PSxXX7s5FKDl//Mn7LublW98/LyShYy\ndOhQ0T8hsJO0DEdWoaYbqRV5+BkAAFA7SZhjlxXlOWSo1xX6dunZ097f1j5rTW2Cr/uGU+57\nF652GWItSkOlN2a8fPmSqIPw9tKRsNK91ZRKTUt7QyScpLJfvswhqs/lWCJiZJTaGNi4Hw3L\nMe69cuNP80ckbrNUKO9DOkfDyqpXLVUUf9KjrLS0AqL21XyMUjLdrfq3XX7rVsTlt0u7fbmr\nxkBTaNtJMeW/an9NteusUN0uAAAox/oRu4xzrgOtva5ID1gVfrYuqY6IiOk6d+1ULf5d//k7\nnorSlo6xMY/ov4iIV8JbBYkXIl8QdTIxUamyVGdjY2Wi+IsXKyxwknvx4g1R2q4St6fHpp+1\n6Gmg24Y7AiIinT59WhM9Djn4ySM2PlW5R3mXLt0g4hobd6+p1Pvk5HQikpGRhJ8MIFadDZWV\nqhmW0+7agtcad04AANSO1cGO//zotH7DN9xsMXhjxKlFJkq1lygjN8hr5ZAWef8s9zovwhoL\nHGuHSZqUd2LF4nOvyx7jVZwaOG99goBj5DjZpOpSUtY/TWhLmYc8fa6XrzeSG//r0r0ZdW+5\nWnKDPJYMkOPHr/U48oaIGMuZsw2l6cFvTgvDXwk/aUyQ/eDUocgKa5lkBnn6XBPqke+y/a9I\nzXbK8A83076ODj6a8Ep4QnvJ6/jfJy06VULcfkOtWoih9yBRpLkc08Ft2nSoMDInLcPpYqyi\n3wvDvwAAdcLmcZX760aN2363mKPZRTXOb/rkCvsMHQLm9atpBEB9wpoFG/5eGv9AlBa5/Xz2\nuF4Yun7HkO43R48dpKPw9t+Th0/cyWxp4btr/lfVlhq4YsfPZ0du97UwiLEfY9aeeXElZP+1\ndoP7q5yIFKX1qmk6rHDytdgYutQ3ZrTvN9IG7kEB8YOcQvytupyxHmltrKVUkvX0XmxEeMzj\njsvu2vZvU1ZOwdxGdesAgxi7MWZazIvokP3nHvK1J21bM6Tsa/dtxKpR7vaqnb/S76TVrqXU\nu5cp/91IeJ5HnLZDNgdMb9/wnoPk4cpxvu6vlpddnPmqoKRIIKsg1bKNrLQMq39/AgCIl4C9\nYhfqVPuxB29/X35c3l9DiajDvNhK5XP+mapZevSYIyI0m5Ww1318Xz11Ja6MrHK77gMn+4Ql\n5wntf7KhNxGN/KtIuFBJWuR6x/56rRW4cjzNr4fO/fPW+wtOrarqVXVKP8WHmycqernTWoFI\nftD2Z6Xv+a/j9y2daNVDS1WBKyPfsm3n7t+OcPbeeeFRfun++CU6RIo/hWX/t891uLGWihxX\nvlUX80lrzj8rFqo1587RNfMmfNezS3u1FlwpGXmeht43No6e++Lf8OvY5fHjxxNRampqHY8H\nAACAmjECgaDa9AOS6aaHrvHKlz+FZe8a1qjt2NraHj58ODU1VVtbu1EbAgAAkBC4xgEAAADA\nEmyeYydmxdmvMrKrXxpfSkmttVIjnc4mbBoAAAC+HIgDdXbTp1cv39Rqd3dYGJuy2pR1TQMA\nAMCXA8GuzvSn7jtnlVftbvmO+mxp2sjngcBHrDUCAADA54BgV2ctdM2sdCWuaQAAAPhy4OYJ\nAAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMA\nAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAA\nAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABg\nCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZA\nsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7\nAAAAAJZAsAMAAABgCQQ7AAAAAJZAsAMAAABgCQQ7AAAAAJZAsPvsnvr3YRjmf3uLazkuwlmN\nYTq6Xf8snQIAAAAWYHOwE2SnXD603tXeyrSbtqoCV57Xrpv5OLcd0Rn8isfl7x3GMAzDMJ3n\nXCmsVEeEsxrDMGODPlun6638U5SS4iqqahkMsFu06/pbQaM0WNfTCwAAAJ+LdFN3oBE92zHB\nwiWKuK30THr2N/ymMO1OzJWgdVHBB8ICL4dO6fRppn30h9vmWVdcdZugr+LC7TpsSn9NIkHR\n+/SHNy5EHvKNDA69fjp2s5WyuJsS+fQCAABAI2Pz1y9Xy3Lulr+T0tMSr/4dejjoZOSdRwlb\nh6kLnh+f6XYoq/LRrXR1VYqu+rgHv22KvoqLvNmcrVu3bt0aELgv9MLdh//M0ZcqTtrivv2R\n+JsS7fQCAABA42NzsFMf471hunUXnlT5FqWvnDa49CTKjYyMrXy00kjvJX1k3gYtWnm1qEHN\nvr99cKmdRVcNZTmuvEp7w0GOq0+lFNRWiJ9+yf/ngd3aKMrJt9QyGuay+3Z2gzpBRESMqqWr\ngwmRIC72hvD1UX7a1W2uY/rqafDkuHK8dt36T1gWfC/34/6bHroMozT5RO6d/W4jemqrKsgp\nttbvN9nvwvMSoVpEO70AAADQ+Ngc7KrE4/GISFZW9tNdXWb5OXWkB5vdtqbUu/r3EQssetv7\nBCUp9Zswx23meKOSGzvdh/YcvP7fmtLim1PTzSxddkTnfWU7022mnWn+8enf2qy7V1JDkToS\nCAREJC0jU76l5N72/xmbO/12Kb/bkImzXWfYW7RKPrJirKmF57WcCiWTA4b3dQzO7jF+xrxZ\n9sbF13fP/66vw9G0mtur4fQCAABAoxNIFH7ymj4yROpO5wo+bsz7aygRdZgXKxC82j9amUjN\nPjjzw74LTq2IaMyRulVfeHF2eyLq5HA6nf9hU9HDrTaqRFImK+982PJkQ28iGvlXUVmpggsz\n2hJJf70wJrtsU07cEmMZKutVnZR+Cp7jOaFP+/r8bD0pIu6Arc/LNt1ZZSRDrQf/9l/ux+Ny\nE9aYKRGnh/fd0vfxS3SIiKS+Xhgt1KPlxjJEapNO5VTfhypPb/XGjx9PRKmpqXX8iCAhCgsK\nHySm3k5Ievr4ZVP3BQDgCyNRI3a5sV52y6OL1Ef7e1pxqzxCzW61u6lMxsFFq6/X43os/+zO\n3U9JfuiyVd+3Zj5sk+40bZ2rIVMSt+PPuKpLlZzd9dcLUrH19OilWLZNwXixzwQ10XtAeVEb\nnZ2dnZ2dHSeMGvhVZ6tNSfzWg/02TWn7Yf/FLZtuFnX+abGdek5GuZx2Ex0GyfJvHT+ZKlSV\nylhPj95CPVro/YMaZRzcGZZXTdu1n94dO3aMF3L16tV6fERgvefPXr1/l1NUWPwq7U3m23dN\n3R0AgC8Jm++KrSj/9uYxQ71iOSaLQv6016juKKbLXD+nLQM2+7sF/BIxU0u0JpLj4rKITAcO\nVK9QZTfLgW3p30fx8ZlkovJpqYfx8e+IBvbrpyS8VaFfv57059+idYCo8N6JgHtCbbcdGXgx\nZIpuWX5PuXr1BRH59W/tV0XhFy9eEHUoe2dcqUfyFhamtPtMfPx/ZGv6Sdk6nd74+PgjR46I\n+JFA4hQVflzksaiotgUfAQBAiIQEu5y4dSOt3c4X9Fxw6twqsxpX/pDrv3zliD2Tjnt5hE3a\nPVykVrKysohIQ6Nyrmnbti3R88zMLKIqgl1WVhaRdJs2qhU3K2loKH56cG14jucyd1iRoCg7\nPfHSzgWOS445D3PtcM3fkkdERK9fvyYiU7fjqwbLf1pYVrvbxzef9ojXpo1s2YesqK6n18vL\na968eeVvZ8+effLkSZE+H0gCtdYq2e9ziEhaRlpFRewL9QAAsJkkBLusKM8hQ72u0LdLz572\n/pZX6/FqE3zdN5xy37twtcsQa1EaKr1z4OXLl0LjXkQfRsI+7K2mVGpa2hsi4SSV/fJlDlF9\nLscSESOj1MbAxv1oWI5x75Ubf5o/InGbpUJ5H9I5GlZWvWqpoviTHmWlpRUQta/8MUQ4vWpq\nampqHz+SomI9oiuwn4qqcjcFufz8AiUlBSlpqdoLAABAGdbPscs45zrQ2uuK9IBV4WfrkuqI\niJiuc9dO1eLf9Z+/46kobekYG/OI/ouIeCW8VZB4IfIFUSeTqq7DElFnY2NloviLFysscJJ7\n8eINUdquErenx6aftehpoNuGOwIiIp0+fVoTPQ45+MkjNj5VuUd5ly7dIOIaG3cX2lif0wtQ\nK1k5Lk+lBVIdAICoWB3s+M+PTus3fMPNFoM3RpxaZKJUe4kycoO8Vg5pkffPcq/ztS5B9xHH\n2mGSJuWdWLH43Ouyx3gVpwbOW58g4Bg5TjapupSU9U8T2lLmIU+f6+XrjeTG/7p0b0bdW66W\n3CCPJQPk+PFrPY68ISLGcuZsQ2l68JvTwvBXwk8aE2Q/OHUossJaJplBnj7XhHrku2z/K1Kz\nnTK87CJu/U8vAAAANAo2X4q9v27UuO13izmaXVTj/KZPrrDP0CFgXr+aFltTn7BmwYa/l8Y/\nEKVFbj+fPa4Xhq7fMaT7zdFjB+kovP335OETdzJbWvjumv9VtaUGrtjx89mR230tDGLsx5i1\nZ15cCdl/rd3g/ionIkVpvWqaDiucfC02hi71jRnt+420gXtQQPwgpxB/qy5nrEdaG2splWQ9\nvRcbER7zuOOyu7b925SVUzC3Ud06wCDGboyZFvMiOmT/uYd87Unb1gxR+HBAg04vAAAANIam\nXm+lEcUu1Kn2Yw/e/r78OKF17CrI+WeqZunRdV3HTiAQCARZCXvdx/fVU1fiysgqt+s+cLJP\nWHKe0P5P1rETCASCkrTI9Y799VorcOV4ml8PnfvnrfcXnFo1cB27Mi93WisQyQ/a/qz0Pf91\n/L6lE616aKkqcGXkW7bt3P3bEc7eOy88yi/dH79Eh0jxp7Ds//a5DjfWUpHjyrfqYj5pzfln\nxUK11vX0Vg/r2AEAAIgXIxAIqv16Bsl000PXeOXLn8Kydw1r1HZsbW0PHz6cmpqqra3dqA0B\nAABICFbPsQMAAACQJGyeYydmxdmvMrKrf3yrlJJaa6VGOp1N2DQAAAB8ORAH6uymT69evqnV\n7u6wMDZl9adPZPjSmwYAAIAvB4JdnelP3XfOqrrnpBLJd9RnS9NGPg8EPmKtEQAAAD4HBLs6\na6FrZqUrcU0DAADAlwM3TwAAAACwBIIdAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEAAACwBIId\nAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEA\nAACwBIIdAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEAAACwBIIdAAAAAEsg2AEAAACwBIIdAAAA\nAEsg2AEAAACwBIIdAAAAAEsg2AEAAACwBIIdA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9uy/0D7Vpq8vNSEF/cvX0geGh67shMRUeED/4G9pp5NktW1GdDPzlggSol/dOtCqGDx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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Dscam</th><td>6.863712</td><td>97.22992</td><td>Dscam</td><td>Glutamatergic_Dp16_old</td><td> 1.2739889</td></tr>\n",
       "\t<tr><th scope=row>Dscam1</th><td>3.075191</td><td>86.16807</td><td>Dscam</td><td>Glutamatergic_2N_old  </td><td>-0.7047110</td></tr>\n",
       "\t<tr><th scope=row>Dscam2</th><td>4.717652</td><td>93.02218</td><td>Dscam</td><td>Glutamatergic_Dp16_yng</td><td> 0.3146506</td></tr>\n",
       "\t<tr><th scope=row>Dscam3</th><td>2.839645</td><td>82.47381</td><td>Dscam</td><td>Glutamatergic_2N_yng  </td><td>-0.8839285</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tDscam & 6.863712 & 97.22992 & Dscam & Glutamatergic\\_Dp16\\_old &  1.2739889\\\\\n",
       "\tDscam1 & 3.075191 & 86.16807 & Dscam & Glutamatergic\\_2N\\_old   & -0.7047110\\\\\n",
       "\tDscam2 & 4.717652 & 93.02218 & Dscam & Glutamatergic\\_Dp16\\_yng &  0.3146506\\\\\n",
       "\tDscam3 & 2.839645 & 82.47381 & Dscam & Glutamatergic\\_2N\\_yng   & -0.8839285\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Dscam | 6.863712 | 97.22992 | Dscam | Glutamatergic_Dp16_old |  1.2739889 |\n",
       "| Dscam1 | 3.075191 | 86.16807 | Dscam | Glutamatergic_2N_old   | -0.7047110 |\n",
       "| Dscam2 | 4.717652 | 93.02218 | Dscam | Glutamatergic_Dp16_yng |  0.3146506 |\n",
       "| Dscam3 | 2.839645 | 82.47381 | Dscam | Glutamatergic_2N_yng   | -0.8839285 |\n",
       "\n"
      ],
      "text/plain": [
       "       avg.exp  pct.exp  features.plot id                     avg.exp.scaled\n",
       "Dscam  6.863712 97.22992 Dscam         Glutamatergic_Dp16_old  1.2739889    \n",
       "Dscam1 3.075191 86.16807 Dscam         Glutamatergic_2N_old   -0.7047110    \n",
       "Dscam2 4.717652 93.02218 Dscam         Glutamatergic_Dp16_yng  0.3146506    \n",
       "Dscam3 2.839645 82.47381 Dscam         Glutamatergic_2N_yng   -0.8839285    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RG9ou8dWz9n/Vkl+31y8rkELmlhISJGVb033XjRGBuw/ZOapnp6egQ74N1CsAPe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X0Q+vXFKd9eaaf6UXJJ+v6jtg63/5HKOG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\nQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# WITH SCT AS ASSAY\n",
    "\n",
    "glut_dplot <- DotPlot(glut, \"Dscam\", group.by = \"replicates\")\n",
    "glut_dplot\n",
    "glut_dplot$data\n",
    "\n",
    "glut_dplot <- DotPlot(glut, \"Dscam\", group.by = \"ct_cond\")\n",
    "glut_dplot\n",
    "glut_dplot$data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d818708b-f526-4c1d-a6af-ff699208a807",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 12 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Dscam</th><td>7.555478e+19</td><td>98.36310</td><td>Dscam</td><td>Dp16_old_Rep1</td><td> 0.5316428</td></tr>\n",
       "\t<tr><th scope=row>Dscam1</th><td>1.598315e+23</td><td>98.18182</td><td>Dscam</td><td>Dp16_old_Rep2</td><td> 0.9126588</td></tr>\n",
       "\t<tr><th scope=row>Dscam2</th><td>1.374820e+23</td><td>98.08612</td><td>Dscam</td><td>Dp16_old_Rep3</td><td> 0.9051635</td></tr>\n",
       "\t<tr><th scope=row>Dscam3</th><td>3.905841e+13</td><td>94.69854</td><td>Dscam</td><td>2N_old_Rep1  </td><td>-0.1886540</td></tr>\n",
       "\t<tr><th scope=row>Dscam4</th><td>1.736701e+04</td><td>81.76670</td><td>Dscam</td><td>2N_old_Rep2  </td><td>-1.2601786</td></tr>\n",
       "\t<tr><th scope=row>Dscam5</th><td>1.022304e+04</td><td>82.24299</td><td>Dscam</td><td>2N_old_Rep3  </td><td>-1.2865460</td></tr>\n",
       "\t<tr><th scope=row>Dscam6</th><td>1.016444e+11</td><td>90.47619</td><td>Dscam</td><td>Dp16_yng_Rep1</td><td>-0.4847945</td></tr>\n",
       "\t<tr><th scope=row>Dscam7</th><td>2.855581e+07</td><td>93.91635</td><td>Dscam</td><td>Dp16_yng_Rep2</td><td>-0.8917038</td></tr>\n",
       "\t<tr><th scope=row>Dscam8</th><td>1.143423e+28</td><td>97.49164</td><td>Dscam</td><td>Dp16_yng_Rep3</td><td> 1.4688803</td></tr>\n",
       "\t<tr><th scope=row>Dscam9</th><td>1.119416e+25</td><td>93.17774</td><td>Dscam</td><td>2N_yng_Rep1  </td><td> 1.1240920</td></tr>\n",
       "\t<tr><th scope=row>Dscam10</th><td>5.678239e+17</td><td>92.90323</td><td>Dscam</td><td>2N_yng_Rep2  </td><td> 0.2882747</td></tr>\n",
       "\t<tr><th scope=row>Dscam11</th><td>2.974094e+05</td><td>88.32117</td><td>Dscam</td><td>2N_yng_Rep3  </td><td>-1.1188351</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 12 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tDscam & 7.555478e+19 & 98.36310 & Dscam & Dp16\\_old\\_Rep1 &  0.5316428\\\\\n",
       "\tDscam1 & 1.598315e+23 & 98.18182 & Dscam & Dp16\\_old\\_Rep2 &  0.9126588\\\\\n",
       "\tDscam2 & 1.374820e+23 & 98.08612 & Dscam & Dp16\\_old\\_Rep3 &  0.9051635\\\\\n",
       "\tDscam3 & 3.905841e+13 & 94.69854 & Dscam & 2N\\_old\\_Rep1   & -0.1886540\\\\\n",
       "\tDscam4 & 1.736701e+04 & 81.76670 & Dscam & 2N\\_old\\_Rep2   & -1.2601786\\\\\n",
       "\tDscam5 & 1.022304e+04 & 82.24299 & Dscam & 2N\\_old\\_Rep3   & -1.2865460\\\\\n",
       "\tDscam6 & 1.016444e+11 & 90.47619 & Dscam & Dp16\\_yng\\_Rep1 & -0.4847945\\\\\n",
       "\tDscam7 & 2.855581e+07 & 93.91635 & Dscam & Dp16\\_yng\\_Rep2 & -0.8917038\\\\\n",
       "\tDscam8 & 1.143423e+28 & 97.49164 & Dscam & Dp16\\_yng\\_Rep3 &  1.4688803\\\\\n",
       "\tDscam9 & 1.119416e+25 & 93.17774 & Dscam & 2N\\_yng\\_Rep1   &  1.1240920\\\\\n",
       "\tDscam10 & 5.678239e+17 & 92.90323 & Dscam & 2N\\_yng\\_Rep2   &  0.2882747\\\\\n",
       "\tDscam11 & 2.974094e+05 & 88.32117 & Dscam & 2N\\_yng\\_Rep3   & -1.1188351\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 12 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Dscam | 7.555478e+19 | 98.36310 | Dscam | Dp16_old_Rep1 |  0.5316428 |\n",
       "| Dscam1 | 1.598315e+23 | 98.18182 | Dscam | Dp16_old_Rep2 |  0.9126588 |\n",
       "| Dscam2 | 1.374820e+23 | 98.08612 | Dscam | Dp16_old_Rep3 |  0.9051635 |\n",
       "| Dscam3 | 3.905841e+13 | 94.69854 | Dscam | 2N_old_Rep1   | -0.1886540 |\n",
       "| Dscam4 | 1.736701e+04 | 81.76670 | Dscam | 2N_old_Rep2   | -1.2601786 |\n",
       "| Dscam5 | 1.022304e+04 | 82.24299 | Dscam | 2N_old_Rep3   | -1.2865460 |\n",
       "| Dscam6 | 1.016444e+11 | 90.47619 | Dscam | Dp16_yng_Rep1 | -0.4847945 |\n",
       "| Dscam7 | 2.855581e+07 | 93.91635 | Dscam | Dp16_yng_Rep2 | -0.8917038 |\n",
       "| Dscam8 | 1.143423e+28 | 97.49164 | Dscam | Dp16_yng_Rep3 |  1.4688803 |\n",
       "| Dscam9 | 1.119416e+25 | 93.17774 | Dscam | 2N_yng_Rep1   |  1.1240920 |\n",
       "| Dscam10 | 5.678239e+17 | 92.90323 | Dscam | 2N_yng_Rep2   |  0.2882747 |\n",
       "| Dscam11 | 2.974094e+05 | 88.32117 | Dscam | 2N_yng_Rep3   | -1.1188351 |\n",
       "\n"
      ],
      "text/plain": [
       "        avg.exp      pct.exp  features.plot id            avg.exp.scaled\n",
       "Dscam   7.555478e+19 98.36310 Dscam         Dp16_old_Rep1  0.5316428    \n",
       "Dscam1  1.598315e+23 98.18182 Dscam         Dp16_old_Rep2  0.9126588    \n",
       "Dscam2  1.374820e+23 98.08612 Dscam         Dp16_old_Rep3  0.9051635    \n",
       "Dscam3  3.905841e+13 94.69854 Dscam         2N_old_Rep1   -0.1886540    \n",
       "Dscam4  1.736701e+04 81.76670 Dscam         2N_old_Rep2   -1.2601786    \n",
       "Dscam5  1.022304e+04 82.24299 Dscam         2N_old_Rep3   -1.2865460    \n",
       "Dscam6  1.016444e+11 90.47619 Dscam         Dp16_yng_Rep1 -0.4847945    \n",
       "Dscam7  2.855581e+07 93.91635 Dscam         Dp16_yng_Rep2 -0.8917038    \n",
       "Dscam8  1.143423e+28 97.49164 Dscam         Dp16_yng_Rep3  1.4688803    \n",
       "Dscam9  1.119416e+25 93.17774 Dscam         2N_yng_Rep1    1.1240920    \n",
       "Dscam10 5.678239e+17 92.90323 Dscam         2N_yng_Rep2    0.2882747    \n",
       "Dscam11 2.974094e+05 88.32117 Dscam         2N_yng_Rep3   -1.1188351    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Scaling data with a low number of groups may produce misleading results”\n"
     ]
    },
    {
     "data": {
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7fpvaoSv9ITEnIkv84M3zpvWwSpOg2y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/6imUv7+6afqwXnJifJyEzKLw2tOFSXdP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\nOg3dFwCQLO+Ss+9Epoirtm59NdW1qk1hAF8KRuwAAEDyiPWpWICvB4IdAAB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kRk9DqgMAqAFT9GoCqLWck/YtB++Qczz34q+BYozJ7O2l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\nyfvf4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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Dscam</th><td>9.517885e+22</td><td>98.22715</td><td>Dscam</td><td>Glutamatergic_Dp16_old</td><td> 0.1558852</td></tr>\n",
       "\t<tr><th scope=row>Dscam1</th><td>1.510824e+13</td><td>86.89184</td><td>Dscam</td><td>Glutamatergic_2N_old  </td><td>-1.4284384</td></tr>\n",
       "\t<tr><th scope=row>Dscam2</th><td>3.159737e+27</td><td>93.66913</td><td>Dscam</td><td>Glutamatergic_Dp16_yng</td><td> 0.8868437</td></tr>\n",
       "\t<tr><th scope=row>Dscam3</th><td>2.512147e+24</td><td>91.70024</td><td>Dscam</td><td>Glutamatergic_2N_yng  </td><td> 0.3857095</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tDscam & 9.517885e+22 & 98.22715 & Dscam & Glutamatergic\\_Dp16\\_old &  0.1558852\\\\\n",
       "\tDscam1 & 1.510824e+13 & 86.89184 & Dscam & Glutamatergic\\_2N\\_old   & -1.4284384\\\\\n",
       "\tDscam2 & 3.159737e+27 & 93.66913 & Dscam & Glutamatergic\\_Dp16\\_yng &  0.8868437\\\\\n",
       "\tDscam3 & 2.512147e+24 & 91.70024 & Dscam & Glutamatergic\\_2N\\_yng   &  0.3857095\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Dscam | 9.517885e+22 | 98.22715 | Dscam | Glutamatergic_Dp16_old |  0.1558852 |\n",
       "| Dscam1 | 1.510824e+13 | 86.89184 | Dscam | Glutamatergic_2N_old   | -1.4284384 |\n",
       "| Dscam2 | 3.159737e+27 | 93.66913 | Dscam | Glutamatergic_Dp16_yng |  0.8868437 |\n",
       "| Dscam3 | 2.512147e+24 | 91.70024 | Dscam | Glutamatergic_2N_yng   |  0.3857095 |\n",
       "\n"
      ],
      "text/plain": [
       "       avg.exp      pct.exp  features.plot id                    \n",
       "Dscam  9.517885e+22 98.22715 Dscam         Glutamatergic_Dp16_old\n",
       "Dscam1 1.510824e+13 86.89184 Dscam         Glutamatergic_2N_old  \n",
       "Dscam2 3.159737e+27 93.66913 Dscam         Glutamatergic_Dp16_yng\n",
       "Dscam3 2.512147e+24 91.70024 Dscam         Glutamatergic_2N_yng  \n",
       "       avg.exp.scaled\n",
       "Dscam   0.1558852    \n",
       "Dscam1 -1.4284384    \n",
       "Dscam2  0.8868437    \n",
       "Dscam3  0.3857095    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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8JFZlGSiwKf3YLoz4uer3KSI+LbzrlTKiEVRC1wkCNS6rbj06RN0fc6kfX08Fyx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\noED0DLX81NQsoqqP9s8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iCGGIaV1qNm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\newAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# WITH RNA AS ASSAY\n",
    "\n",
    "glut_dplot <- DotPlot(glut, \"Dscam\", group.by = \"replicates\")\n",
    "glut_dplot\n",
    "glut_dplot$data\n",
    "\n",
    "glut_dplot <- DotPlot(glut, \"Dscam\", group.by = \"ct_cond\")\n",
    "glut_dplot\n",
    "glut_dplot$data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d7bb845-e41c-4be0-a492-07ca944349ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# THIS IS THE DESEQ2 OUTPUT FOR DP16_OLD V DP16_YNG\n",
    "# log2FoldChange\tpadj\tCelltype\tGene\tSignif\n",
    "# 0.565760343\t9.30E-06\tGABAergic\tDscam\tYes\n",
    "# 0.573405339\t0.012150718\tGlutamatergic\tDscam\tYes\n",
    "\n",
    "# slightly up-regulated for both GABA and Glut\n",
    "# ~1.5FC\n",
    "\n",
    "# OK OK I THINK I FIGURED OUT THE ISSUE\n",
    "# with the scCustomize dotplots i was using the RNA assay which are the raw read counts\n",
    "# deseq2 outputs normalizes the counts across the replicates\n",
    "# when i make a dotplot with SCT assay that is normalized across the replicates it checks out in the Dscam Glut Dp16_old v. Dp16_yng case"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a089f7af-5d26-44db-8f9a-62b157684f17",
   "metadata": {},
   "source": [
    "Normalization: DESeq2 normalizes the counts to account for differences in sequencing depth and other systematic biases. This is done using size factors that scale the counts so that they are comparable across samples.\n",
    "\n",
    "Dispersion Estimation: DESeq2 estimates the dispersion for each gene, which reflects the variability of counts across replicates. This step is crucial because it allows DESeq2 to model the counts accurately and account for biological variability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6557b67c-5f98-4046-bb90-c9df3ab2b75c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pR3TufEXM3XL1sTVY08n3fndI5Cql9Ew0aJvyuOOJGfmSBpOWlL5KXKbh/Njwkv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wfb9cOIgoMdNUACudy2iWPhGIBNBMdQsPvbHSdzci5f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wSCjx9/ITLjgKH387+/zhrvDhgsc57uec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\nDN2QmQ4ow+yJ7NxkPO5GfRkXE6Zxb415tG4RjxOEnqIoYHF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uf6jT1RNDpAyH0gAAIABJREFUeO713Vt/PHH5QUKenOBLJZyia59O2TAq\nbUtQg0+aMWNG586dq1/u27cvKiqqQSsjiJ04TBaK6ym+iGXlqmISZ1a1C5eju4XhAbFTo9JN\n4mzeQ7RA0mh7gdSSEU7oUP/6WCCeDEhcjByA1NXC8UzshJXm1oTaGBjCl1jSlaPxZU3Ayc34\ndlMQOXA9/KRCiQ3CRSw25tlaqteSYkdr89t5QpbEiVtRrnX3tdBGu3ZXHB6mVRMA4OBmVXIW\nm4sKHbDKcgIAxM5Mi1UdAIjr3plcAfrvqjoAuHjxYrNtCgoKoqKievfube2H4RH7Vke8ePHt\n6k86Lth75pcZbaovSlJSEgAEBtaTb35t2zIhLjk5GcAu7Ow0wC7sXh4QUcdpbwfNu/kIAKEe\n7D+U8P7aOsKJvLfv1wQERWiKptVljfXSCAablBrJhl/a8V2cxnPRhXu/DKsJOSRFr2qwZ/nN\nVaMnbHlUyXbu2GfgWFeWqiTxQUmpOv1muAyCGthvhYSEhITUlHxdv37dRGHH5mI9R3irFXqh\nlG2lLQVXiPUa5VKYpeGLMI/WFgZU3HwQ7zZITkr9YJt3G8TNx7zD8w7EuAJEozQStwvsbsk3\nVOiABfbiJz2qWqnJzY/tFWihXmnbnRUTplWU1cTtWrVnOnlaKOw6hPDyU3UaZVVvXYcLLJiH\nBYB+I9DfdlF43ecLNgf6DrdcE6Ao4tPGZgU/tuoKRZHgfu42WYyBgSE9hrmXFWj4YpZQaq1t\nUL8JjpnxakDAL9iqkKRnW45PECc7QQsATDbSY9S/72NnYn5IamqqdcJO3H3uxsM9xw7o6Osu\nporTY//+5cu1P987MHuUyOvZjgFVX9iKCgUAQyyud5FRiUQIUC6XayxbUcbOq41d2L1cVK3k\nznOBJwf3R67Z3rPmLf3f+4/mMof0c79xP5vOi8qCd1o10okRFLdvxwJA69atqzaUZWZWAvTr\n06f2D4oRV5ScQ3MmbXmE9l159dT64Z4sAIDKo2Okc/4CEdPWNxeThYqdbJN/I3JkWW+J9/Ya\n5s6PcUVZjSATOSJvrzF7jpjBBKdWWM6z+lljFI14BVl4EYMHCr0DObIinC/BXHwsP1MWF5n4\ngfDBBU1eCoExwb8zq9frHLBUY/BEjDGLHXMSdbiOcvVliZ0tPDtnD1j+DWP3elL5YmVRoQSW\nbmA0Fsl72bHVYgxMNsPN1wYZhADA4TPa9baBCQ6CQO+xknZ9CK2KkrpiLcHHjsk06StsYrPG\n8Z60qsb00qfDkHd/7N9V3Lvfpsc/fXPiqwHzm1a4NE0DgG0KOOy8cvz73yI7RonY9eG2s7HF\nddz16YqYSykAAOzebwxgZB7Zf63W24qz+0+VCcYvXNaFCQBFvy3anagFAIhbE4Aggnnncu8d\nXjO9f4CLkIU6TTpWQlRtD1U/P750oI/bm8dlABxF7Lmb+SQAgKu/Px8g5lpYftrlbe8M7xLg\nIeEwvZfd0AJA2o17hlymsrvrFnx+qYI/cufZbwyqjiyL3TVn5V8ksAaOH2Yb77OWS0mmztdb\n7eaOi8SESEy4u+O+3uqSTLPXoT+7hwi/jBQVM/U6FGgAAIpGlEo0L5+5axWRm9ZoBl7TSFyZ\nrTrwrFF1BgQS1NWP5daa496G6+rLZHGsGkswFuLXidOmO89iVWdALKZ8fUipmBQJKAcR4d+K\nFIksvFB2/nXETphrK1ZLUHUAEBTUMIXECB06dLD1J7N7LpjZCQB/9Cj2xSaxWARAVlSo6rak\nKiqUACyx+N8vNLHTArFH7FoopZEHPjv8w0qhT5dePYJ8nbi4vCA16uaDdBUA8IZ98s107q+z\nf9t/fsf2qvaFJ/aFqhznLpwkPLkQgOAqr7zXJeDo+HEhoidlANozM3xO6CT+AweOmtYt7uyp\n2Z5uXo4qADx0geexEgVJU4AIfIKkhWc+Gx799PTDwxNdRyz7oP2Jb45PDfid0NACNx9HDEh+\nm9acpLTikog7eTDNGaDs0K6wUkAESXtmDD+sLsrNLyoqLK7EAXV//ac9S+pnAL5apD/Gw89o\nAMDZpSbSRtMQfkYtdET9O5n6NJ+VRP99nAQArRYp0GIoQqMMIEjEoPB0Gji6FV+5xzz/FABI\njdE/uqypKKF4IrTTQHaXoRZa2VWU0sc2aUrzqiZP71+ANt2wqR9zMIvkIq6j466rMp9qCT3t\n6MnsPlLg6GnJT1BSDHVgnZ7AQfBiGqq8iN7/pW7RJnZA5xYhDv4LqCsJBIArtHYQoUg6P1Wr\nU5OOnmyJy7/vMj1hwoSPP/5YqzVi7VlNx44d/wFh1zAlxpBd9zApKQmgW612mSkpOEDHtm1t\nfwh2XgHsP4ItlKGbb53fs/6d4X50XvSVP349+FtoeCbWceSgtgDg3M5FMvmdydLKc/v/kBma\nlxzZf4PwmbVwhGGlAea4rbuXj/YqvnXs+8OPFABkpc556N7Hz26dO7L/4OGdq94Z256rxQHI\nsmIFy63j8Nlrj0ZlZz5LvPdVVzTryDufX1YDp9eGsGtf9uBpCEBRBOG2Hr/xWmL0ur4A0Gv5\ne4aEXZVAAAAinvLJnWu3Hj5NzSmuxAEAEXq197XCWbcxVAp9YValTtOIpZ/JkDj9MFR+9vui\nq7+WluU1sM0wjci/NY2+dbnRtxpy60zdQlEaIYgqVWcgI4HOTDCvNjY7AQ87oqoooQBAraAi\nQjVx15sapZogdK+2WtUZSIkhws+ZHZU0EHGhMjlSo9fSFAUlOfiNY3JVhSXlumd340bsTvRw\n9hcL/5otGZVCX5Rdqddae9sDQFZCRfS1gmcRJTqNhVXSBiiSjr5aEn6m4O6ZgpjrJRRleayU\nwOlbJ0uir8ji7ypunyxJizW+tt7/Jx4eHh9//HHTbbZt2/ZPfHSDlBjwHTLEDyDl77/r5P3l\nX778GMBzyBC7sLNjDLuwa6FwPXqMf/fL3X/eik7ILFboCL1KlpcUcXZhm6r3OWMWznTXX9t/\nbVIETVPryg5F0x3eXtjnxd+TG7T4f2cjUosrdZEr/ADAafavfy40OFQIus7evPfMnT+W+gKA\nZNqfxfmPrx7ZMKubFAFe1xUb3nKC0pMHL2oAMI/XFr/VEYA15OfU/GfXD346xJ0/6xxN0/e/\n6GAIlChoLQAoy2R0wFs/30wurqzIfXJh3XD3yshtb0zflWXsvK5evbq1FomJRpYyM4pKoY+7\nk5fyuCT2Th6BW2ICUk1SpCo7QUvo6YoS4sFFefM7NECnoUtzGx0aS3NJncbUoS71afPnkvrU\nvIHzWXh9D5f4BltMQaui0x4bOc34+5aIDK2Kyn5e5zD0WjrjidkHJi+lC7OMX7S8NKoJG5qm\nIXAyJT6vMEdm2e71SH1a8Dw6h8Ct0k8AoKzQxd7JTXlSEnc3z2D3YzHFOar0pzJFua44W5UU\nVWpNVzlJyrKCqkeF0lxtXoqq6fZNkPVMXVnL8eT5/UqK/Pen1NevX//GG2809u533303cuRI\nKz9CHnn+wpOSWl8kqjRq1+ylx2XA7DN7eo2lQbcFS3oxIfZ/nx7JrrqZqKI/P98STjG6LH6n\njz3Fzo4x7FOxLyvYoHfmtvlpy4GDCR99WbjvUCra+3/zOzbauku/fkaNF7oOHFgnl5o7YEAP\nOPx3bOwzmNYDwH38jEFr7l9b0qHrX9MmjXhtQEhInw5uNWuXkiQJACTS6ctzR5e0QwEAgsd9\ndZab03b4gVvf7Y5auqWBl9358+ct87GrlGkNgQFcR2pUuFBi+Sqota2zNJWkBS5cuvqLdDRo\noKJNXONVaYKwVFWYN9RVltdXAMoKiiSAYebXXV1J08Y+2dzjqToGmRGVY3Rj06gat/0DAHUl\nLXKwZLhTyNXyMlVlhcbNu0Ett5noNHh5iRIAFOVqB1erUk2Vch3QAAjodaRWTfBFlmdMKuV6\no/+3AFUF0cRLa7qiSFpTSfIl//LAhGHYqVOnvv/++02bNpWV1VgMBAUFbd++ffTo0dZ/hPz2\nNxM+i3Fs3bGdn5e7iCzOiI+Jy1bSDM/xu458UNuqqvWHB7ZeDPn47Ntdup2ZPNgPzbl79nx0\nsaD3hgOfdLTrOjtGsUfsXl46LVzYE3l26MDN0P0n8lnDF872AdAe23BYBUAUVLfKuZ8DAKkZ\nRmusMFdXh7pbxK6ubICKiqpqw9bLLkYcWzWxTUXY7q+WTBkS7O7g3W/u9/eqHvelUgkAgJi8\nsiDYQ4AhCIJNPw38YROHCwCyooxFBRYsWPBHLfr27Wvi2UpdeEwWAwD4IpY1wxsAOHvX7C5x\nscSFiytEkMZ3QlDgikz6yc1OpkyJ7T1/RDWceWwCqVt9OxKxE2quqgMAoRQxupfExZIBReyM\nNczzM7eEgqLgebi+iY9/dl9PWxTYkjjw3b0d/AKtsMJ7AZvL9PRzcPEUS5ytLUGVOPMwNgMA\nBGI2T2BV/pnUlWv0/xYdVe0vIF33pbld1TkpJhvliVpEuAFF0Y8++qigoODWrVuHDh06evRo\nXFzc8+fPbaLqAMBp6NJV74xtz5Onx9w4f+F6TA4aMGz22qOPnp57p03dvzOr40dXos99Na2D\n5v6J3T8fuyPzf+OL3yKvr+1m9zmx0wgt4itkxzJaz1342ppFh+csU8r5ExdMa9I4y/hQSBQV\nlQPU1nYVRUU6AC9xtQ4UBs/cfGrmZkKR9fjBnbBzh3YdOLJ8dL7gWdgCb2gb6INACl32JDze\nK8jTqSi5yLCPRCIGUBrNPu7WrVu3bjVZwKdPn37w4IEpJ8vmYj2Geqsr9QIJ25r1xADAvzNP\np6Zzk7V8MaPLEEsCKqnRShab0mmMizsWm0qNVgb1babn8iJ67xocDAGZJ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NDpjMTmi4uLly1bNmbMGJnMbIeX2miPTUQa5Y0/apIX4te0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r2Txah+689mEc/YMiGU+pEz+pi7MpAOg7qjbM\nVphJJN7Fzu9R95vAGDwV1zOdPz9NkhZXLarAAJrG5zKeSMsLJH5hQne/tofhmnLq3A5JZTEJ\nCJqr/pIkVlFAnvlZEjKA3XMMR89pUHEVkfZYnJmgrhczyk9VPDyr9g3l2bsZEE2sqURX9iuf\nPyBYHMq+Qc4GXT2kun5EFT6U0W8SC9c73EmoUdojaVq8XDv9I+m2VClVdoziW9vp9SJCCC7s\nU189TIBWxQmtjyEtgfr2XeXQGfiQ6Qb7/QqZGgBUCoIiKDrdpAAnQVAqJUFRSCUnTHfsZGIV\nRSG51AySeAqZmiIpmdgMBQskVbWCmeIqI/W91SoUc0H9+IqKxVa6eAMAEEr0w7tijwC893iW\nZwfLUhgLFozEqEU9gqAJH341QdcHo7dcsoStzYwyP78cABwcHKAN3bjC6moR1MXjgCMUNh7G\ncRwHIEmN/0C+2PlRWhGPiysqEk/9lHDyJwDAhZ3GrN3xy9IoezMeqAmbN2/euHFj/Z/z5s07\ndepUS6deVaK+c0IkF2ssYdIqnMGilDI6ACikVMJ1ce5zRdR4obZmW0vcP0+c/FlN1Kk3Jz/i\n+wTKxNV4eTEDAJRyuHRAnfWMnLOGxW5LWSL1cVXOczEA8KyBzaUUsoajs3kU14ok1PD8YaWs\nRu3f1aYVO+Iq6sQ2sUwjVIgBj0+JaxoNZnx+7SVMuK5QyqgB09texpv6SJwaK6EohDMwDMM0\n024sDlmSoy7JUXgEcIP7C/RxhQszqGNb5JJqBAAqBUaoMJyJAEAmoVMkUCQ8OKvOeUZO+Zij\nT6RTVEbcO1UlqyEBgMmiqZQ0AMAwYLHJgjSiKEPRqbeVf3jbZ3fsW9XDS7XXBGGN/TrUILV3\n6QBRUwmT3jXMo3L2tMYwjGvFZLBMdSkYTHqn7q5qFWlta7w0TD3tgxzF1QqBnRkUTxxcrZgs\nnGdlfO1gikSZidKMRKlSRmjc+sJU5eXCkvahfO8grv6/ssoLqGNb5VUlFADIcIaVDcnikGUF\nLJLAsp+R2c9kEUOZg6azTFk3bcHCK4tpq7Uplbi6qkbGsHU3xwvMgi5Ut6/dVgF4du/uDEbo\nxumyWFINoHh45iTXK7L/uNdcrFRFqc+ePk3OFVUnn3h/uMjq2ZX5HuY4kC6a1MxmMluM+dRU\nEDcPV2kXclDJ6Sp5ozd9ZZH65uGqQbNsW0/VenKX/OP7RhU5yooYZUVNzyE1njrwpWr+emYr\nwZ68FLHGq9MQHFUTf9tapaABAJNNhUTV1O+b81zM4eMeAbrnQCkSLuyUyLTkpz09VKmpbLW6\ndn9bO0Jo0xALef5A5eiJB/VubUhOuiPKTKytyETDkZWDmlLRaAyqfnTMS5HJpWTkKNvW08iq\nS6kjX8lldTUnEMJKi5hsDoUoUGhd/8Is6ujX8tnruK3H7WoqiOgjFWpVrTWhg1ouo1MkxuKS\ndBwBAEXB02gxqUaBPVqLcd4+TdR7dQC1nhyG1WYlosaS6PfPE26+WM8RBrzfaHTMxdvIqsHa\nVJVJSwvEMrEKIVSSJ7JztnJw5ZuS1oYz6DYOZhA6BgAMw6xs2HS6kSmqShn18GxlVYkmdoip\nFbUnJReTT2+JCtLk3UbYsjhtG68qofZtkMkltfeMJLCs5KYDSOwllUKGRi+yrIixYMFgjPuG\nk4W3tr8zMszdmmNt5+zuseBc7faaq1/OnTNn/UUzVDW0AAAARMq3a/eVAXSYPq0rQK1uHDy7\nebNMu5VBunHlD1OrAbhdP7mVl3n/7LE9v/5+6OztxJzKirTr6yd4g/jaqesSsxzIFBAF906K\n9CnPJa5UP7rUWnliaQ068o2+JTuTY8j751qcWlLIyNS4RlXSbJ3UfUdXhvcXhfcX9R1daePY\n6ECpcdUKme7aTcn3lGX5jT5is6mgILmPj9LdXRUQoPDxVjbxBR6clSua1QqrpyBNXu/VaaDR\nAGdTTWIe5fnKFw/aqLT71y9KWeNKYojC5FK6orFXjQEUZVHRx1ubIiQJdO9UVb1Xp9mNwyN5\n1gSONzpE8j1JaU6LpiTV6PyepjcRIaAoQBRQFDS/Lud2E9IafSvgkCRVUVpTkF1enF8pEcn1\n3Ku5kRfxRc8fF1UUS+RSlUKmriqTpT8tefogX6Uwcr4SANQqQiZRkIRpZfTkRNqT0kc3ch5c\nynpwOevpg8LKUsPqr5EEuv9XRZ1Xp4PKIlXM2UpNQedWoEg4vk1e79W1wtPb6vi2KiS+bFJT\nUy9durR3796DBw9GR0frI1xswcI/jhGOnfzxlsHB/d7+8Vx8QdMim9adrHP27934wxmd6VUW\nDALVpJ5dP2Lgynty3HfBdx91pQEA0IbMm+UG8rOfrbxSUfdmJHJ+X/ZNIqKFzJ8T1oq9OtLu\n3ScBG/DOfNbjpAVMvEkAACAASURBVIqG4YZm3b5bd6EagMHl4g0H+mRovx4dnK3ZTI7QPSiq\nz9gvGx0o5WYugPROrDrvwmfTonzteSyOjXfEO9dbc7T0IuuJvKZCz7EQy3uuqCxqcQC4cZww\nqFLqpYME0YKx7Gc1zcctnIkc3FQObirNZKU2FImyn+m6FggeX9FR+pNGQ7a2hJOTun4SVhul\nDCXd1p0dRZEo+b6+Fz3ziVQzK6qTjEQy97kBhURjL6rEVS1e3sxEmbRaX2tPols8hVunCaWB\n7pZcgu78pdcjVF0pSXqUlZVSVJRXkZ9V9uJJbtqzAkJtcDXVtCcllSU6athLRMrkx4VtejzN\nkYoVz+NzEh9kJMflxN9Ly3xeqFIa4yBKa5QJd/JK88VKOQEAJEHVVMqfPyrKSzfgRZ32WCIq\na8PNqixWZSTouALaPLmtLs3T10m9dVxpXPFlE8nPz1+2bFm7du0CAgKGDRs2Z86cGTNm9OvX\nz93dPSIiYsuWLVJpG6dpwcI/iMGOnSL6k3Ef3Shn+Yxefzw2veyPWY3mCFzGjYsE4tqZCyYU\n435Vkd/9btGiRYsWLXpz7owpI3sHuTp3GLXucpFtz/f+uPrTkLpkLWafjfs+CGJn/PZap25T\nlixf+fHCUcEhb56rsOn9hZ66cQJHBwBUkHd/19RgV/fQYVPmLvl4zacr3psxoPP43wpYnZYu\nHckGAGaf5cvC2VASHx2Tx/QKCe/sok6/f+eFGBO8tmpp4wPJbk6KGLM9xbbn5HmzRvgp4i/e\nyAJAJlUZz35m2DCenaS7RDpCEH/TsJ6Iq1Bago5dEIKSXIOf65IcGWo2MJXkEpIqYwIwmYm6\n4yWlecq6TMS2oUiUl9LiiSTdNSxGQqjhRUyL3kZ2kgH3UVRGVBbrPvqTO8Y8Tk/utH2R5VJl\n5vNCtarRKYgqJZkpRQYdq6pMqtOr0yATq4pyqlv6tKWOpSTmScUND3ZlmTjlSS5FGvbkIIRS\nEkoJtY69clMrxVW6vzhNoEiU2ZbHpiEjXoJa7WBitAEPmKQapev6Mr481Gr1qlWr/P39v/nm\nm6ysrCafIoQePXr00Ucf+fn57d+//+/smAUL+mNojp3kj2925oFgxM+3Ts9xB4DiJtNFLhER\nbnAvJSUHIFCnAQstoXpxdscLAKAxuXxroZNnx+FvvDl80szJg/ysG11k6wFb7z4M+3LT9hM3\n9247qWY7tO86Z+MHa5aN1FM3zu/16f4/bY7/bBWj16DeysqcmIsxZyvlDDs3r8DJG79a9vak\nIA4AgPr2V988UoBDcB9v+Yvn8Y/UbAffyB5E0v3UC19893yilo4dFD0oWX37+YbuQgwAqOID\nw31mXlagPCMntAAINaooUKNmqx5boSRbt8dTUYSqSg3+xZ+eSAVGNE3bltWoVXKDxxiVgpTV\nqHmCRon8JdlGjlVl+SSpRs2rpJflGrbOsSxXGRChO/kv55nBfct+RkYM1bFSQSGlasoNizCV\n5ihtnZuakolRaZ4xYZuibEohg9ZXw5QUVFGUDuM1VVKZRMHl65vjVVrQxgR3aYHYrV1ri2ma\nUJhbQVFNXSSlXF1WLHJyM8BOTaVCLmlx/rQ4r8bKpu1zrChUqVV6OZRKOVVVorJ10f0yUilQ\nQZphD1jWUyKwu8mVu/SjvLx84sSJ0dHRbbYsKiqaNWtWTEzMtm3bzFBYzIIFs2LoE/n43j0l\n2M76YI57Cw1cXFwA0gsLLY6d/rBnnEUzDNnBusv0z49O/7zFz0M2pqONzba2X52AVgMAqIIP\nKt9YtuP29XwAAGAIvbv06zds8vzFM3q51g2q1OVde/OBM+Lry63p2AX084S7GZ6LvlnbvW5x\nJM15+rKpSy7vZod76Oral19+efz48fo/MzMzm7eRiymEDKsOL2shXlVdboxDUF2mYy9lC9ly\nbaKQkU0cO6nI2HwpBNIaZN2s1L1cYljfWrpciAJxtcFXTFyp+3RaOkoraK8mqUdUYfxknKgc\nsT1be5SkkhZDVlKxAY5dmxoicqmKIpH+60ZbSvWTiOQGOXbSmtaSIFv/tKGZyAAHXVpNtOTY\niatQ8wB265hy9w1CIpEMHDjwyZMn+u/y448/1tTU7N279+X1yoIFIzB0KlYkEgF4eXu32ICi\nKACFQq/4voV/Bqb/lO9u5RS/uHls+8YP50/s5SZNurhn07zeHXp8fLUu6UajY9dJp44dZMXH\na00r6daxq9KtY5eXl/dYC52tkK4ISuu0NPvTXBxOH5oFSgCarbvUn+anY1yv6vbV0Y/WJ790\ntG/hZBAy5jRbOh1DewUt3HpTLhfZVmZbK46GQT6IPidrmMEW75Fhd6j19npaM+hW6vz61H5k\n+K00IjfRCBBCM2bMMMir07Bv376tW7cadUxZ0p/frHln5sioTq58HMMw/PXjLTVVZJxeP71P\ngLM1m23l6NdzyuqjOpMp9Gxm4f8eQx07GxsbgNzc3JY+J5KTU3XJn1n450Hi1HPbPpg2KLSd\nsy2PyXYOH//+D+eSKf/JW29nPD34Ziem+PHmmWtuajJgWtWxg+pqUcOmBh279C9DMAx//Wor\nOnY//fSTdq3iyZMnN2/D1kOXrgktSdlZ2xpqSbOXjrAKUw8dB52wuE1ndU3R1ucJdHSDzTOs\nb2yebn0wGh24Vgb3jW+j++j66As220VHx3TeDj0RNItuNj0it0UFGQ7PAL03Nq8N2TwmC6fj\nBlwQLl/30Vva3hKcVjvW+qcNzawMEJTjWrfY2ND6LgBgZft3FGb9888/T58+bdy+q1evbmVI\nbJnSs58v2/jjgUtJNfZu9q2cpCrp26HhY9cdTmJ1m7xw0fRe1uknNr0eMXBjvNyYZhZeBQz9\nzoRERDCg4q9Dl3Un0pYc/OWUBHg9e1pKT/y7QGU31g/2Cxz5wbZjsdX2wQPGTp89bczAENvK\n2EOfvzWsY/BqYs03s+0Biq9cSQKARoJ5jTBVx04fmGyawMGwJAEHD93jk6MHjWdt8Fji01HH\n94JnzcAZBo8xdBzjWTftm72bkUk5AgeaTsU+O1fDBnv7ltu7+xusCevRQgkvrjW9lTFeJ/bu\nOqbw+EKsTf9MJzaOWJt338FFt3IPh8fiWxugCWzvwgfQobrSpIH+OLvr+FFCx2ktdbglhPbc\nViSXHVz1qjVn78bScxKZjmMtzcMCAIePObgb9iX6G0pQEASxcuVKo3dXKBRr1641fD/7MVsu\nx6aVSarznmwd1rJ/nfHd/E9uVduN2RUX/9dv3337y5+xTw5PdRM/WDdv6zNkcDMLrwSGDlRW\n49+YbAtFvy+Y8XOcqPFHROGVlWPePSsB1zlvjvgXVXK2AIrHG0aMWHet3HnoxgtpxVkxl44f\n3P3brgPHzt55UVKaevH7N/2lBVIGgwYNgbZ/WMfOo4NhwqQttafRIKiHYQ85kw0dwnXsQqNj\n9m4Gy6U6uOsoeubaHmdxjfFUfDrrHjKdfFgMlgGn6RbQoqC4EYnqHbq1uItB95HDp9t76DhB\nDIOgHsaM7vrsZS3kuvs4YI0Vm1kcpm+gq0Giwg6uVjzrFmWyGUy6QSsnAMDahufTwQVnNJwC\nh8v07+zBYBp2g2h0rH2Q7sqw9i58O2e9pI9xJubRQS8Req9OXDre2oULijJgcGCwMP+uL31p\nwp07d1JTU02xcOTIEcMFUPiB/QaHt7dvVVsdIO73n2NUEPL+ljnetY8CzXnS5uVRNDJhx84H\nyMBmFl4NDI5AWI/9evskN5RzanF3n4De47c9UAE8P/LJWxOjfNsP+eJhDeY9b+eGfnqXkLTw\nN5D50+KNsXJ2t02Xz6wa5pP403tbTsaX1uZMY9Z+Q9/55c7BvifXHyoFEPbu7XD31w2Lxvb+\n+JIaA/nZed5ePaet+eO5DLQE816rmYxh/DlnlfkplQDyo5OYNPexY8MxvxWJAOTRd9YkApBH\nx2HY2ANGJlv6h3NZXH0fTnt3hotviyGoQa8z6HoPDQig7ziczdP9rvXpZHCgUucuNDp0brWG\nhE7oeIt7MZg0vzB9A0JufhyhQ4uDa6ceuL2bAa+FoF64nWuL7f0jeEy2vtY6RvFpLbTtMw7X\n/yZqoOPQZ6xe+zi723YK83ZytxXY8GwdrDx9nYLCvNkcw15iGIYFhrlw+Tr2YjDpgV1dGUyD\nfVM7R+vOEe38gty9/Z0Dgj06dvXmWRlTicHWiRfU3ZVn3fDw4Ayal7+tf4hjK3s1ITDSmq1r\nolwLxLWmB3RrIwQYPoSh/4Rs99cYRuQGGEorVQ31RKFQXLp0ySydaUL29etZAH7Dh7fX3uo2\nfHgXgPzr11MNa2bhFcGI9AXXKQduH3sn0g5Vpd45eT1FDZB84utfTtzLldNsu71zInrHCKPy\nmiy8LBJ3/xZDgP20dUs7MQCgPPb3j8aHudp7hQ+aMPONhQtmTxkV5deu18roarrn5O2fjYjd\ntvCrC8U2IcOnT+pmT6dkeQ+PbJwcHNBv0sh6wbzZ9gCA8vZNmHFCBIC59Z4xrmf4pM/2b5ni\nCUCLnDXRE4AWuXT//vejjHTxcSbWfaReXhSTTes2orWWdi7YsJn6BgncfGgDp7TYmG/D8Oyg\n19SVBq9AK76Nbmuhg9g6s+VaoUtftnXLqTi+oXwnr7ZHfb4Q79K3tctFo8PIBSxcvwtmbYsN\nmt6ah9rm3anHowPbO6jFmJCDGxY1yjDPrs9Y3M5FX5+AzWF6+Dj4Bbm36+Dq6CrEWi251hJM\nNt6lh4envx2bW3v5mCzcxVsY0suTLzCyPCsdpwlsefbOAisB15S6ZAI7Tkgv9+6DvDv3cOva\nz7P7IB/39jYGGWRxaZEjbVvKzgQADh+PHGXXph/PZGPjlnDoejxgHgH0XmONL2urP7GxsaYb\nefjwoelGmpOSkgIAAQEBjTf7+PszABrijHo2s/CKYFReKtNn4vf3c9Ju7NuyfNHMSWNGjhr/\n+rz3N/126XnWw+/HeVo0ff5l3L37AgDvO7i/5h058PObp3esf3OwDyp4fOnYnl2Hz97JxoOG\nz99w6FHikanu0P/bnNLsB2cP7dp59GFG3IEVk7p58Gjq/OhT96jQORvPPLr8cTADAEB2/c/c\n4a97ArB7vbvrxLHV04fPGBNiA4B5RQTbAGBefWfM6OtjfOKzsw8zcrSg9WkdNp/WZ7KQL2wj\nFjJgMt5zZNvPpZ0LNm8dk9mqd+Tf1cbOVa+oiZ0r2y+sxdk3Jhsb/gYPb6ZI1xKu7fHIUa3N\nhWEYhA+zcW3fWhuhI6PnWLs2J23d/emj32K36dvxBNjkjzhtRl+cvFmRo4Wtn6lnIKfr0Db8\nv1HzGb6d9X2c/EJoI+Yalg+CEFSXyxUyk2pY0eiYezubkF6ebu4ujk5OwT09fTrYGxGr00Yh\nI0rzJToVhg0FAUiqVGoVZZiYUB0CB0bfKfbuAZwmDiGGgWcgt+8UBytbvd7+noH0Ce9xmOzW\nOuHdiT7pA46hYVrj0CQOm8hLqjYmEtUA0AWCJjPmNKHQCkBVXS03qJmFVwRDvzcJvy/5NY5y\nH7NhxRCffjOX9Zv5UnplwZwUFwOAnbt7rTvCcQ0fvSB8dHePt39+GFHfyHHY3KkhQgAAO3eN\nAB0iZDVq50Hvfjfw3VW7xgevShj51ZXdo7WGKPvpX/2+d/jhQ80O6FwnmKeDtWvXHjhwoP7P\nkpKSVnruGci2tsMTr4tLdFUR9Q5id+5rpc/SSwyDiUsYLt7Yud0tlhfr3JM+eSmjzVx7DIPQ\nfg4pj6ryUiWtNPPw5weE27QeEHHyxl9byLu8S9pKBVgNnoGMIXN5tLbcAzqOhQ+1KWzPTokR\niysbCY9x+HTfEL53EFfPFPiOPXBre87ZHcryAt3+hE9n+qiF7OaKejpx82ML7PGk25LCdEUT\neQ2+kN6pl5V7QNu+Mh2HNzawDnylevagDc2Mzj3p0z5itnm5mlCQUZWTUkmjY137ezFbXm2g\nD7nJsqe3RAAgqyG79DUpHRVRKD46n1BRNo6coB4uppgCgBexZZUlchoN6zbUncUxxmli8+hd\nh9gE9RLEXiwTlasBQOjECh9ixzJwzbhfKP7G59wbR5UvYogmjwTPGosay+w6yOA7aDSVlZWm\nG2lB3+llodGpaTPmqmczC/9nGPrdzr7yy/ajwoWTtr+U3lh4GSA1AJR8t/LAllszGu531rUd\nOw42jJC+wkUbxmpUp6vjd29Yt/34jYQ8cSPnoKCgEkArCzukZ08DVg3WIpPJtN+AanUbARKh\nI973dRtRGZGbLM98KkYU0JnQIULo5scydMVl1Eg8pA/97lny6R2iKJuiKAwAuNbQuQe92xDc\np5O+IxNGwzp0s3Vpx0t5VFNVpqBhDeMShTAbB3ZAuEBgr9cctEcAY9JH1ndOyrKeNFwH7ZIb\nLA4WNoQdOoCN6T1uuvpyXH05iTdEWU+kCAADzM6V2XuSnb771+HuR1/wFTf5ARFzQVmSQ5EE\nBgA4TrUPZXQdwvQJMuzi823wyNHCmnLiwm8VGAaas/QN5XQdYq2/ERYH5q1lPrhAXDpA1FTq\n8IYFdtiwWYxuQ+hGDGSa+hMImaBYWG+KbPoPo0F1GnKtiMPpD1VrymCV4CawuDSONU0qRgDA\ns8YM9eo02DjRxr/LkVSjC79XisoRSWAMJurcm9t1MPdvc+k0ODg4aOSdTMHR0YCERf0RCKwB\nqkUiKYB2NI4SiSQATIGAbVAzC68Ihjp2Tk5OABjb8pgYg+LASM7Mc3V/0Zg8K2uBo1dgl7Ae\nQyfOnDLI3/rlCDa5OAKkA8gbu1BjDxDoAABA8Y+9XN65W7dZHfdZ/16fJrACB/UfHlCWnZVX\nXFJapQJMpVKnRN8vXzi6PsuL6+oqAABUk3zqp69+PHY/JTu/XK4GoO4d3HO/14wezjqfrc2b\nN2/evLn+zylTphw7dqzNUxA44J37Wjn70iuLFc7ePIG9kZk3PGtsyDR8yDQ8J1mSniAR2DNC\n+tngTGOuu8Ce1W2Yw/YPZEq5isGmAECtoLG5zLe2GubtWtvTXnuTX5ZHbvlUBTK1kI/YTFQj\nw0qr6P1GMUZNZ7KNWj/rH8EvzlJKRSTOonWMMiAvUBsaHYKicN9g2vkdVXIxBQgcvRiD53D0\n9zKbYG2Pe3bkZD9VAGBsHi0w0jAFEADAMOjxGh4xCE+8Q/y1Q6VSAEkBnQZMNox9i9m5J44b\nu3DLo70N14rJ4TGZbFPn/7yDuIhCaiXlE2zwCTaBRsNC+rhWlyvsXfVavto6HcLtS3Il1rZs\nNtfUcwwIFyJUjWHg39WkkCRfiPUez42/VkUSSODADB3I+Zu9OgBwc3NLT0830Yirq6tZOtOE\ngIAAgIcpKSkAYVqbs9PS1ABB/v6GNbPwqoAMQ3FyugCwyG9zDdzPAkJIvn8EADA7jFy4cOHC\nhQvemD1t4mtRHZ04AACYfeSSExnql3HYhBXtAUA4/rBS58dFP0QBgO8n8QghpDo53QrAbcZb\nkQAATDv/yCFjJ03o663x5DHX0bsySYTiV/kC8GafQaj60mJ/BgAm6DB0xsL3ZkfaAAAGgDmM\n3pOlT980AsU5OTnmO92/lZJc8vt3ZWvGS9aMl3z/rqwklzTaVFERCg1FmhgNk4lWrTK1byRB\nVZep1ErKVEMIKWVU2mN5dpKCJEw3hoqzlNlJcqXM+GuloTCDOPSF5PslNYe+kBRmmKNnFv4h\nVAqypkJFmeFRNYbVq1vKHDGAy5cvG9+DM7NZAPQpf+j46PEKHwAI3ZShvbHgx140ALd371EG\nNrPwamCoY4fUz7dF8cBpzK9pipfRn/9rNI6dYP6VRlvJ6hen1w5xowPQfeZfqHgJx03fEoED\nsLt99Uyl49NGjl3RtigAGPrdgTVLt19KrdYMloXbB7ABwJYPANzxh6obHLuMr8MAwH7soQIK\nIYQyvw4DoPXs7QoAHu8/1KNr/3XHDiFEkqg0jyzNI0lTHRVEEOjWLXTiBMrMNEfPLFiwoAcx\nMTEmenXW1tZKpe4fznrRimOH0r/uxgCwH7c3p/a3C1l8fLo7AD3ks6eUwc0svBIY6thVpN6/\nf/67131ZwHLv+9bnv+z/82L0vfvNSH0Z/sl/Ht2OHUIIIfWLr6M4AOD/SUzt17LOeVLlnt8w\ntWc7Oy6TLfQKn7j2XE7j0ETRnZ3rF47p2dHbyZrNYAtcAvtMXX0sWardJG9zEAAA0F2HbrqY\nJavdSpbc//XDSb39NAKZdEHA4NmrjiadmMkDcJj+Z/0NJHIOTnQCAICuIzsDgN3CKw2O3dVF\nQgB4bVetTdGuIQDQbdYIHIAz46wel+T/wLGzYMHCfxqKorp162aKY/fBBx8YcdycE8tnaxjo\nSwPAvPvV/rnsSJZWM+XTb3oLAGg2Xca8+d7SheO7OtIB+N03PJY1sqZnMwuvAoY6dn9M0Os5\nn6Dzp8erTiuOHULKq4scAcBj6QPN3/GrfAG4A6aOcWI4h42c8daSNyZEONEBaO2W3tJ22/6Y\ngHE9u4+YOvftD5d/tGTe2K6OOACv51eJDdG5vG3dASCgoyMNAOgCn27DJk4fF+XOxgAwOg0A\nMI5zUN/+wQ6Mvj/kP1zRkQ7A8ug36/2Vaz5ZMKqTgO4xZVJPAOg2MQoAXN+91eDY5f8QRQdw\nGH+0SPObMGtzdxyAxQBgd5i44rPPjj1tY4LM4thZsGDhH+fmzZtGe3VCobCiwphQRvyqAN0W\nvZbFNm4pSz+1dmovPwcek8mzbxc5aeXh5xIdBvVsZuH/HkMdu/NveenDW+dfSm//47Tq2CHl\nHxOYANDz+0KEUK1jB8COXP2gqjaSThbtHycAYI3aW9OwW3lerqRRpF36aE04Gzgj9lfWbdE4\ndmP2Vbw4883S1wcEezvyGRgAYGynkGFzVvx8KUVEIYSQqjivWIXUBTe2zOwd6GrNZlu7dBww\nd/O1Qsn+MQDg7YUDOC68otTKsZM/2NhDCEATdhw+862lSxfP6OfFxmg4g6FR1RizX976JTHI\nsSMJSlSuNFciTk2lklCbx5ZMrJaJzZAfSZJo9Wo0ciS6ccN0Y4hQUwXpStNT2RBCiEKF6aqK\nQvPkgEqqidIc8yRUFedRl48SpfnmuY+VRUq51Dy5enIJIanWlflgOBSF5FLzmEIIiauUBGGe\ny1VToRZXmueRUCnIqhKzfbWN4+233zbOsTty5Mg/2W8LFpphcI6dBeNp3bFD999zAwC/NYkI\noTrHzvPde9pvTurSXAGA09u3m+9NqaXV5SXFRUVFRYmbegBwZp6uG6JqHbv9dZaoq4scAJh9\nvs/Su+vSmLURHADH8YeKmn6keHFoYbCWZgU3YOzqQ4niFgx9+OGHNlowmUz9HbvE6LLL+3Iy\nnlTr3e0WKcqUXN6XE3Ox2HRTChlxZX/elf15pvsEJ0/WLp5wckKmD3JxV8WHN5Vc3VfZdtO2\nyE9R7l1dtnd1WXWpqedIEtSf35Qd+qwk55kZsnQ/GKOa3V350Xgz+D2FGfLTPxZc3lNMmuz3\nECrq6sH8i7tzayrN0LH0pyX3LqQV54pMN1WUJbl2JDvuuhkee0m1+vQPBad/KJCKzOAK3z5R\nfG5nXt6LfzK+pFarBw0aZKhXt2bNmn+wzxYs6OTlCGxYMAbUXEuSFhoRpq1LgHl6ujeVwqyO\n3/3BmAhPAYcntHdydnFxcQledR9AXlDQkupm5oMHZQCBw4d769cxRdKPE0asj6WFLf9z91Rn\n7U8SPnTD2IHTjggWHXyYVSaVVuY8PvGRV+ymaT2iVt7RKXbO5XK1HTsGw4DyABpxXbp+Ertt\nmMJpZjNFwzAMNP+ZCLNOqoPBMIM1Oh0AgNZq6Q59TeGY5v9mkKLAMI1aCs0cRQU05TGMljjR\nRlOmFqOBcVUZGtuqtdZS6VuDoNPN96zSsfr/m2qKVmvKLOokmgfMLB0zGhzHz5w5M3OmvqL7\nLBbr22+/3bBhw0vtlQULxvBPe5b/Nap+Hdj2ReXNv6Br39Yjdopj45kAEPWDJibWMN2pTdpn\nwQD0KSfr/lY93hDCAbAJnvrx5p0Hj58+e/7ChQunlnUHgKhtebWNGkXsnurO69AVBZSnn1o3\nraeXFR0DwFiu/ZcdedFoUQaSbA+lA2A+KxoFE2Q3FnoA0Ltvy271SiKEDJyKpSgkrTGbIoxc\nQphr6kelIJVyc8x4IvTNN2jmTBQb23bLNqEoVJavMtd0c3mBuqbSPNOUShlZVWKe+1hVRt05\nR4oqzDS3WKlWKc1zH9VKUmGmWV2EkFppNlNyqdpcj71MTMgl5ukYoaYk1S9F7MkIdu3a5ebm\n1vorPjw8/PZtHRMnFiz8G7AUdjUQpv/Q2bPdG/6ueHT87DOpY/fJwzs0VOlkR7XxWtCB6va1\n2yoAz+7dndtuXIf63DebE+RuC/+6+8ugBv3SlMcr9NjXNmz8qM71yrWCSKcm/Un6dmjv929V\n43QgGS5hPRzzbm19PeJuWvT11aF1Zxp3O50EoDt3aVQ9gNN7QCRjxx/xjxMo8DJnSBjDgGtl\ntie2lXLmhtJm9VX9ef99c1kCDAN7N8PqpbaCnavZrjyTQ2MaVaugOUJ7LOo1s4V5rGzMdo44\nk2aWOGKdNbM9q6ZLE9fD4ZutV3Qc4wn+LYPR3Llzp0yZsmfPnpMnT0ZHR2tXx7G2th4+fPiU\nKVPGjh1rqdNl4V+Lod+lB1snbrnfdrMeHx5fFmlUh/7tcPt8tKeP1t+PPrx59pnUb8Z3e5YY\n4JA1g0j5du2+MoAO06d1NWC3iuxsMUDPyEhtVfqi69dftLEfnQ2kxKrf+j3veLXQIuO7+Z/c\nqsbpQAj7fXH5zPIwbvEfM8InH143b+u4uNWdNK80lZoEAKRoUo2nqqREDcBjmc/dsWDBgoW/\nDS6Xu3jx4sWLF8vl8vz8/KKiIhzHPTw8nJ2dDcoesWDhn8HACJ9F7qQJscu8oGH+VJu6uVRF\n2okV4yI8USuVqQAAIABJREFUbThsK4EVAFjNuYIQWXjtq9l9/B35LLaNd9igEZGudADcd8Gl\n2kx3snjva0IAGofLYrCsXTr0mb7m+HNpw1RsrfG/jo9lAeA8Pptt5Rw0/P2jKdJ62TkOn8di\n27SLmrv9/BdNp2KZXbzoALZDtz/XXrWqKskrqU32jn3HCQAAsx/63dN6GaT8H6JoAO4NOubV\nnwdgAMDptef6vmWjwjxsOCyuvW8nPxsMgDvmsB6LHCxyJ02QSlFhHjJd69iCBQsWLLyaGBqx\nC33jhx/6NdtKiIsyUx5dPH45jQyYumJJT9v2oQba/X8F5e6b0OP0k/YjBk8LVyf/eeiGCCQn\nV00trDxztYDt5iy0E8oLcuKuZgNm3e29vUe3DLEBAPLFr+MGLDovAqC59X93QkBN1sOzf3w2\n8dS5tdf24I2M7/89nmBgpFTOdnJUvLiwbcqN3Tw1bsfBQI6sgieOFD46cW734qnBfk27xYkY\n4VN65tLiIIcvQ3oP6NPFRlaQ+ujqZatVhTeW2APcXLe7BAAwhw62cVvemlO3m1gmBMg/czn1\nux4BAACCof3tVqaUy+/MGXiX7eAX2D6QV5iS+qycAprrrI8nC1765f2XoFIgAGCyTZqaQQg2\nrUB7dwBJgqs7bP4Z69HX1I4pZRSTQzPLlJFUROEMjGVU4VptKAoyEtRyMdUumMEXmhTTrSpF\nF/epC7OQWzts2CyG0MEyNWbBggULBk/F+g5bsqSlz9SbrqwcP+77w2kLYpb4mtiv/xdkN85U\nr7+X9GlXawBQhKVw3oxBopgjlwGApq6owIROfr2C0PPr8aW+494e640DAHq+eerbZ4jIoe73\nLlVGLfr6y5EAIH+yeXDUx58t2LUEa2S8Zv29p31ub/r092uJWTQGHRQiykpg1bMnXLrrN3Hj\n70sd31nTLWzjk8Im3VI/PP4XAACQktzHF/Y8vsQUunXqPnzFGwM12XJP82UAAKj0zuG9d5qe\nU15qKoBmBQbNTgBQDpi1sxtLnP0kDji2HmF9bIvvxeYf33Fpa8/hXHNezIJ0SWWRwtWXb+fK\nNtFUSbYiPV4isGd0ihIYXdJew/P78rirEgAIG8QP7MFps31LHNoFu7bX/rswHxbPRDcSMaGN\nkdZINbp2QFSao7aypQ+aJeAJTUqHevCXJDVWQaNDt5F8/3CTLv75ndLMJ2oAuPeXYupyK4GD\nkVefJOC3NcqSPAQARVmQn44++IllyipUQk0VZYu5Vgw7Z1OfWoSgIF1MqCh3PyucaWpCAklQ\nUonCSsAxPamLolBVmZRvzWJxTJ1PVMjI5Ls1gEGnKAHLtIxJpYx8fLlSUk20C+a3D7VqewcL\nFiy0ijmzoBhug7/et7LDi+/nb3iIzGj3P43Xwi2rutauLWC/8fDOUhcAsJlxVoZIpVRUVpD6\n+MbVP94PBvQs8QkFAAC3tn+foG43+4sDcWVl2Vsiy8vLy8vLpa4z5w1kUU/ueJ5GiDgytsF4\nt4B+y/bdSi4QyZU33nEBJMdHfnXyDkLozlJ3AGbInKnBgGQANBYLBwAQdJ29ce+VhMyiarms\nMifp2o4lUY40SiVm9Fu1ff3EQE3Ct5M/ANCnn2wa4L28wBaAkFQ3VjIRTt6bmlcqVhKEUlya\nHhsd/fN0eyg/suuMDsGTt99+G9Pi2LFjel5IqUidfL+yOFuWGF2GTH68Eq5XVxapsp5Ki7J0\nqrLoC0KQeEOKKEAUJN6QmtKxW1cb7SyqhoRY463lpahKc9QAIK4kU2MVxhsCkIoojQWKhMRr\nMhNNabw6AFDJUUqsymhTJbmUxqvTUJxDleZRpvQt61llZlJl0v0SaY3xvartW4405VFlxpPq\n7GRR263bIvNF8YuE/KLcqrabtkVRTnVqYnHy46Y/9IwgNVaSnyrPT5GnP5aYaCr7mbSqRKVW\nUikxNUq5STfRggULYF7HDgCwgKFDvCHzxIl489r9z0ILjQjTjpW4ubkCQKfwcE6jjW4Aqvz8\nMgCA7Pv3iwAyt/R1aIzL/NNKgKKiIl3GqYIrX8zsNWt3KQBUHdj0e7G2cRcABODirlnL6zFu\nxapZg4J9nAVsjo1npwELfrh2dkUwTmb++MWhNkch1FxqDwBC+/Tha//N6d07HEAVH/+suQUP\nD4+uWtjY6BuSouM0jcwVzjDD3CLOrDVh4oJWDIDOqDWFM0zqF7tZsI9lQmiMwWzoC84y6Xrh\nDKgPauJME01h2ipxplhjNDsphol9Y9IBgEbH6Lipb8X6h4rBMsO6USYLBwRMlhkWjTKY9Pr/\nmwiTXXeOpmUgAACjLqhJo2NmkeuzYOEVx+wrzAmCACgtKAAIM7fp/yIcgaCR6AGO4wAgEAia\nb6xdVV9RUQEA4R/+9cVQHdN6LE+fAyOxmef4Ia5axrO3Tx+9Mto6LMIRYos6TFzYs3Y6g0z6\nY8PeXbEAAMLXJkS00EdWxPzpXTYlxsXExMO8fgAAIBBYA1SLRFIA7fW2lEgkAWAKBLUeB5KJ\nFAC0jF+GBH6ZmVMsZ9h7d44aMWfZcicnFoBIpMNRXL58+fLly+v/nDJlip5BOzaPHjrAQVSm\ncvYxw/xutxF2OUlSgQPDwZ1lkiEMeo61enRRAgDhw/imaNuOnoSdOd4QgvJqByEt3TE9cPNj\ndojk5D1X2rkxOnQ3foIYAFhcWrcR/IRrUiab1mMMv+0dWjOFRQxjx15QAICdC71TT+MVQexd\nMf9QWmp8bYCnQzjd1tkkn8A70EZoz+bwGaYLgti5cMIHO6tVlJ2LSVdeg5efo5uPHY6bwRtz\ndLO2tuGw2GZ47ft15TOYGEbDvINM/T56deLJJYSkivAO4pv4y8GCBQtgdsdO8fj0pXwAFzs7\n89p9hdA4faU050GDdI7ripxmmyRXz0YroO+23WP3BMcW+Y6YElbrjakTDm78MZYNAO0XfNyz\n5XstFAoBQKlU1m0ICAgAeJiSktLYP89OS1MDBPn71/5dcPJUAQDkZ1Z3i+rbuZuqJDnm3vGt\nd08cDAlSArgLzLx6wtaZbetsanadBisbPKi3ebrn5sd087M13c7A4bBlB7bjW1ReCl27w6rP\nMY4pXgEG4cP44cNM8sPqCejGDuhmnivfYxQ7MJKpkFCOnrgpRQswDOauZd0/RxRmUW7taD1e\nw02M42IY2DiawQ/TILA37QdDY8zi1Wlgc82j1kHHMd9Q8zxddBzrFCU0iykLFiyA4Y6dSlxe\no2y+mVJWl+S9uH34640/PgdwGD483Cy9exXxjYx0gMTcP4/c+yxCz4BGYWEhAN3ZuZl3wZ5x\ninz9yFjG1NN2Dq0MyzXR0fEA4Otbv+TFe8AAH3iYdvFi5udh7RqOc+FCIoDbgAF1jh3T2VsA\n+SKrEVuuHB3LBwCQJO+Y2n/R2YQkAGZoaCe9um+hjvFTYfzU//+IhdCBBsaumdCGwYQ+4/4t\nqrYWLFiw8C/B0NfrX3MddOHk7telx6i3v79dROHe0375bLj5RNdfNbABS97tjEP6Dws/uV6m\nnU6PJOnnj0aXNG794ENvDAtY+xSAPDrO4/2HAHBp93UASFjdHsP4c86q8xJSAODxynYcG++I\nScu//e3UkzKiwQBVHvPF8NkHqwBozzZGeISMWLr7ieTmoiFfZLFoEL/tw325ZJ01du91dyia\ns+2tmU5WTJr7hw/AcWBfewAQnVi38aEUAAD4HRd+PsUFAAG7z9xRZot/WLCgk/IilPSQKi/6\n1y3WIolaERwLFixY+Jsx2+9dOkvo4hfSZ/TcDz+cGWqsRoMFAKAFrTi+I37gwj+/HeR3cciY\nIaEefFKU/yL25vWYXO9Pn49pr924/bRv94ek/bni45OFkUu3+Z5572BGlz71gTKUd2hSj2NZ\nAGDXbWIv1fVTx796fAbQYjvfoA4+7i7WZGnWk5j4fAUAxg0Yt3BSIF708M93oh4PCCcB7PqE\nSm+enBsS9ufE/vzHxQDKzHIcx2RKQfdhU/pIa9zrYoDcXsNtf+kXFPP6hCgPrOjBH/uKAIA7\ncMlrZtU6+ddSnk88f6AAgMBItr27SV+omgoq5rxSXEl5BzFC+jNN1GFRSKmKArW1A25lY+pE\nnqyGykhQMlhY+1CWiVlQkioq8aZSIaV8Q5jeQSZNC+7fQl45Rmr+PXQqffr7Jp1meQGZmaji\n8GgdejBNWYdBEnBxlyLpnhpR4BOEj1zI5gn+/6OwJqJWUQopyReatv7IggULAGC4YzfhmFqt\nYz06Rsctq5nMBt1/3vHEsMPffrP79M2zv90QI569i6t3yMz166bM9IFGunL2YWNnhL1I//Lj\nk0VefceH33/vYIaLb33VV9n1kyUr1w38fM1577FfH/8APzAxYOZJqWfXAG5lZlxqTA3B4jEJ\nAJrnnCvPdg/QJMysf3ddn4j11QCCrj88XnplzZZDVw/9XK0iAQBo7eZfiP5piHP9AJoAAID5\nLjyzY+qny7cc+/FIiZJtzaaB2nbG0uE6z00mk2nl8oFKZYC0hLhaLqqQ2btYsbmmRoQLM6RZ\nT8VWtoygKFuaCY9udSl59ucaQo0AICNeNfY9gdDRSPeCUKHjW6TVZRQAZD0llHIUOdL4PK2a\ncuLq/kq1EtHoWM8xAjd/403JxdTJb0UKKQUAqbHKUYuNV/5Tq9DJ78TiSgoAUmJUr73J9+5s\npG/38CpV79UBwKXDZIdQrGs/I3tWlkue/K6GJAAAMhJVY9+xMnodzN1Tyqd3aiVdspKIi7sV\nE5aaFLomSVImUfCtuWYpTioRyzgcFt3kpD2lnMhOrsIwzLujDZNtokutfHSxgiSQrQur+0g7\nGs0ylFiwYBKGvgcxGq6LV9erC9+SjRC6o6NQbMjGdIQke0Y22ui+9AFC6OycRhlv+OunEEIP\nPnRv2ITZhkzbsO9KYm6FVKmSVRZmJN07/fOauf28a8dnete9+hj3XPDN+tXnao3TnKcvmiAA\nUhn51ZPMwgqJSi09NAYIEE77/ocB9WnQnC6fbJzlAAAALN8x6w7dTi2VKGM+9gYA+xnffqPl\n1WmdI6/jtK1/xeVWVdz52E8qphzHf79+kG7f66OPPrLV4tSpUy1e2sYgBCnxhQVZlZnPStpu\n3RbPH1RJReriLFlxtknCbLnJKo1XBwCEGuUkGy+BVppHabw6DamP1K00bpPsJIVaiQCAIlF6\nvEnnmPdCrfHqAKAsj6gqIVpv3wql2aTGq9OQFmf85XrxuOkPzORHxk99pseryLrTKsogaiqN\nV1PLSiK1/8xOIpFp0my5mcXpL3LLiitNsgIAAFWVNekpOdmZBaabyksVleRKinPE+emmavVl\nP5WQBAKAyiJlZZGpIoIWLFgw1LGL37lo0dK9T1tuIL35zaJFi3ZadOz+duSJX8zs1cHDlkPH\nMKzfEQlohO60Y7KYp6c7QFVVndRpRny8GCC0d+/GMnS9enXVeYSQnj1bm11VJP04YcT6WFrY\n8j93T23u6GoICAgYpIWTk1MLDZuCYcBk4wBgumg+ALA4tf4pm2tSsKGJiJcpVcVYnCZ/mvRj\nSbsn9ZJjppsCAKYJZQaYWieFTDtHDr/pvlwT1mhqnyOGmdSxJveRwQYTp9Q5XBaNTmNzzLDM\nlsVi0HE6h2uGBc713yAWx9R8Hu3n08Rn1YIFC2D4VGzG5R07LipGfju7cwsN5El/7dgRPWHQ\nLwss5WJfIqLfBwvhSvVvg+q3oPubVpbZRM5+c6q/DYvm6VX1KQBHKGw8GuA4DkCSdSGFmpoa\nANzJqclyWp6TEw+aw3V1bSYQIkv685ejN+Lj4x49fJRSrkJg8z/2zjMuiqsL489sZ4FdepNe\nRUFB7Ni7wd47mhhbjBpLYprRaGKMGmOKUWNHsbeIGhs2VCyASu+997Z9d94Pi8BStyX6vu/+\nf/sBZu/cOXd2Zu6Ze899zvj7t7f6c1o1fMWKFStWrKj/V3kdOwBevez5tSJ9Ay30cN2Gmeem\n1Bqa0E2sNerkXH2ZcY8F5QVSACZWVFdf9W0ztaF69KAnPhcDoNLQS4N5WACufuyiLHFButDI\nku49UCNZCvvODHtPRla8CIDPUD1NErya21JduzFSIkUA9A0pXYeof/J7D6fcPCUVvZnVZzDR\na7j6hnn1Z6ZEicrypQB6jNbTJCWuzxBGRmxDOhPfIZq+h1h1MLPqYKZhJXLY+nrePu7tl1MC\nWzcjNodBACaWmsbSevTkiASy2kqJfSd9jql21Fh06Ph/RutiATKZDCA0ydmoQy3IYjEGbrpy\nZIm8C3j51Yb29+FwOEBmYWEZ0Ni3qy0srAWadSUthfgUhXy/ZksEqEwGRCQAyuA5A/6xpTMU\nCqFvqB15MDaH5tZNCzp2dCYxcaVRbrIIQAc3hibCbAACFrG9+kmqy2V2HjS1k6jKodGJAdO0\now1GoWD4fMPqMimNQegZaHZnExgxX997AFPII21caAwNBsbs3YmV22nn/pDmZZAdnIipy6i2\nLhoMs7GJqes4pflSPX3CwFijNnbsQZu8Su/1A7FEBI8etK4D/zc9FYKA5kl15TDZ1O6jdMqn\nOnRoDa07dtnZOYChoS6T81uAamWl2ou9i4+PIaJfhoXVLBrXMKgjCAuLULYGs/E7zhoe+/bT\nw9F63t2qoyOl/5u9WFtQqLDrqB15H6kMJJ0qo1OlmqSw+GcwNNGaRq61s3YeO969Kd69tfYK\nSaHC3FY7bXTrRnPrphPY06FDx9tBqadPbVr4kzR5pufoIkCa/+r27eZzKKSEV5p65/eD6UBf\nL5007b9G+Nqhm+RJWaWnJxKnAYD7wa17VgD4R8ca4Er5ZuoPn205cvNlTi2NTQFI3ptgburI\nebMsgvYFfxzA+1MSH5OaU1AmYhoZykqLmxwj8V4WIA57LkyVfPfl9uDQ11kl3BWPc3b0rEoM\n3rDmcILRyN23F0V2nxz57zX7f45X4eSv38hy0uv+HTqBWPolxUDLyTvURyYFhYJ3x+EkSTwM\nkd0+Ky3OIy1siBEzqH1HayGJsA4dOnT8t6OUY5d+bOHwTY0Sut/8avjNNoqbTFo+y0ZDu3Qo\njeusLyaeWn4xF6D0XnX0Iz8ADFcvhMi/JbODp/Y497TDyGHT3mcVPTh14TXIu0ce8ib1ZwNg\nDtu8P/DCxKMPLhSaObk5du5qmRsfmyMXVq0ubbqYjxc6udeWJ2b9+7/RsUveOXHqn/ESSgc3\nk8gde8IkgOzp7/PnhwCA9/v71gzQZloleXNkJKENNQSJmCwvELI5NH2upiMr6dGC5Bd8EHD3\n03P0VjNoLCsFXy+SiQQNW+5cIsuLZd8fVnNESiYlk57zinPEHFOqZx99TWLSRXzy7ile+msR\nlUp4DWD2GauniXuXGSuKus0X8kmHzvQeo9lUmpp1XT0mPbunLlg0I5Hcv0lSVU4dPVtrw4qa\nQ5L433Y0K4pEBEFwzTUdpS/NE0c/rOFXyaxdGN79Daj0/+mzpkPHP49SvRrLwq1z3RBcVXZs\ndo2RvWeHZnOtBJXB5lq7dR8+d/nSkcouddShOWbdhnYxwsU8gHAYOGfOBPnWl3WOHS/0YuFX\nD+O/7WVEAEgydfDYllXz9/Zz1f3nGQKA+fiD90522Pr72RsRSTGl5u7+8/df+ax0hu2n8RVP\nHpajZ+OAufzHWcuvx/7coHjy4lSpBIAsN+zk0Tp5vYx7RzMAACP7/daSY1dSUlJVVVX/b21t\nrZLNlIhlUaFFVaVCK0f9Tn3MNOkyxSJZ2PliXpWEQiG6DjG2cVFfZiw/VfTkcl1zSnLETH2K\ntbM607J/HVfw6uREPiJT40kXT3Wa+vp+TeIzHoC8FJQXSAbNVD/y8fElfmqUCIBMSkbdFnDN\nKJ36qumxl+VLQ4/XaVvEPJBSKETPAHXitGqrcPFPaZON5/ZKB42n6qm7UKS2SpidXM7SZzh4\nGGuoGFdVKoh9WiSVkO6+phZ2miZUlcs3mttwNF8PXlMpzEuv4JjoWdm3vr5JOV7dLc9O4AFw\n9NL36q9+NKeQJ7t/ukIkkAGoLJFIJfAboQvk0aFDI5Ry7FyXXYxZJv/z3BRi6t/jf49poqCm\n41+DNSeEjzF6c682bOq4MSYeXp6bEhoV89mSEgVX3+9S7Rf99I3cqwPg/kPGjSLjkYefPXuF\nef3k26idpn8XNP07gJTwqiprBGJpzDYeCZDpLx9KMY4KAB6D7PEo1WzOtm0KOnbdf0ghf3jz\nT8h81tijkulnJaemtGH+N998s2fPHjXaXZzDryoVAijIqHXoxDUwUr+TK8kW8qokAGQyMiu+\nVhPHLi9FIXNybrJQPccuM6Xl7VkpcPFUoz7kJjcYVpgpEgtJOlNNZyU7UUFRLytBorZjl5ci\nlnt1dTUniNRz7PLSSUkzmT+JCHkZpIuXms3MiC8rL+YBtRxjloYrPXNSqkQCKYCM+ArNHbuk\nV/kSsbS2Wujho+lESHpcSXWFoCS/xshUj6Wv/h0klZA5iXXiiJlxvM7+XLXH0UtyxXKvTk5e\nilDn2OnQoSGqzkP1WH748ERXn3/EFh1qk3PsQCxAZDYdxGhNyi65XsoONSUltdlXtm3cc+7u\ny+zqxtqzorzcMsC8YUNzHbuXX7n6flcQeKWpVHLr+Pr6Tp06tf7f8PDw7OxsZXbU069rBpVG\naCKlBoCl3+Cc6ulrNHnHZCtYwmKraZheK45Ea9vbhcmm1JTXXQ40OkHTYHqLpU9UNxLH1dPX\noCpFGRGWvpqni9WSHE8b25WBbcgoL+ZRKARLX9PZ+foa9DSuCoA+h1lZyjPgaEF8jm3IqKoQ\nMBhUOlOjy55CJegsiogvA8BkUzSJjmAq3stMde8gHTp01KPqc8dh0Pz5/4QdOlRA8Og5gKqH\nkcCwVgvxYu48LQOIJ184GczPr5VS68bSmkjZIfwjl1Fnq6QUOoMKCoVKIWQSKWng4FSTmd44\n9xda1rFTmYULFy5cuLD+3+nTpyvp2BlZML36mVcWCyzs9RmadUvGVgzP3tycRJ6+Ma1jL43m\npNz89NJeC+QulIEx1c1PzcG/7gOIZ/eaJk7QY8Oru5pdZteBBg/PV8hTivkMNdREI9d3GOvm\n4boZczqD8NYgctKxC8P0Aa00TwKASiN8h6l5umydiQ7ORG6awhmzdydsHNX3MJw6mZpa67P0\naHIdbE1w9DSmM6hSiayDi6YzngA6+naQiKU0uhbCB128zC3tOHoGdCpVI/+JINB9pGnC00qC\nIDr21qiNZrb0Dm5M+QAzlUZ499fAN9ehQwcAzeROZLySvILSKr5Y1iyVD9fey04LjzQd6lMU\ncvB2OYByvpmTWWFSa2m4xCnptVISkEokJEFQ6AwGKeWJZNJmAV8t69j9q1jasy3ttSOd5dzV\nwLmrpnNkAJhsynuLTPJSRAQBaxeG2gNjo6cRD68T0c8V7qQlX6m/KtbcnjFmqVlFkcTQmKZn\nqFEv7urLMDCipL0S0+jo2JvJMVW/NhqdGPcxJyNGJOSRdh50Q1M1nRWCgmVbaDtXScqK6s6Y\nmRWxdDNNwyuUY6yFUTEAFCph567N9cxa8erkGHC1s6LJxJrRd4J5++WUoP8Uo4J0Eb9aauHA\n0Oe+Q8tfdOj4L0Utx06QfH7rhu1Hrr7Iqm4+9wcAmHyWPNdWpJWOfxyz8atn/f5hcPmsw6+n\nnGONPdpKgs+Ia/FSgO67N+n5YkcqAFnB2Tm+007m/6vG/jdDoxP2npp2lnQGth2jXD9DPr5F\nVpTBwQ2TFxAunTTMKkaxsNeOwJ6VE83KSTvCbFQa4eKjBd/C1oX44Qw94p6sOI+0sCX8BlIY\n2vHKdLwFrJy0c6Hq0KED6jh2wpffDx7wZXg1QGfQIRUzDI1Z4qoqgdzFo+mbcFkEOFrXudCh\nIgae3Z3a/xUi/3pWA4BhZ8Gpe1OmmPfyt6KfLBAD1fXjR63p2L3pSnlxwRs2h4gA8tz7HgNC\nPtz0/SeDbXSv3ipBoSJgJhEwU6f1oCxMPfQdrQvJ0qFDhw4FVH4spv22dEN4temgLffzq05N\nYwJjD5VV8vkVqWHBX49zYZJGfTfczCo5NPafMFaHtskIDS0EGETtXzN9Bgeu/nLD+sXjunZZ\nWdjRCAAqm+gU80In95r8+0u616jpcyb2tWUBgAQQXl/q6jtvX7IIAPRo+Y+Prhvq4TFhf8a/\n3BgdOt4ZBHzUVLVfTIcOHTq0jqqOXfb5M+FSwvfTA18OsGI1jC3Quc7+M7+9/OL6Mu71VRNW\n36rWrpU6/iESExMBDPjs+7k9DZIu/fHT7mNhtT2/uvn8Uw8KAH4Txy7/cdbM67Gx9y4dO3Do\n/JlVPgAgBSRFOfkiaU15NQmgprxaCpA1qVd2/8Vr4YhZWVkRjShvWJ7bPgXpwqjbVZXFrcwq\nq0JtpfRlaFVuUguhhGpQUcKvKOG3X649+LX48SPxxyOEN0+1EuOgCmKhLCuhmlethdMFIDel\npjRPC20EUJonzIitkUmbheaqTmWx5GVoTWWJFtr44o70i8mCncuF1RWaGhYZRgb2l8ztJwk5\n0VTkWw2EfElhdrVUooWqZDKyKKdGwGsmFaMWOUm1eSnK6lC2TWGGIO5xlaBWC5e9Dh1vg4wf\nuhMEwZof8rYNAaC6YxcfHw84DB3qAtRF0zdaYAmjwdu+n2qQfXjXWRW6ax2qwvLvAYDTv1vD\nJgtbAOM+Gt+4mM+WFJJsJkTi+tVLkpSckusYV1ZWAVTLXp8fexCXW8nnV+bF3jm0dkgHy65G\nAHoPeJOZ22OQPYBmOnYAmACMpl+sJhvBuxJoBlnKwyst+AHbtm3r3ohbt24p3+5n1yrTXvNe\n3dPCSEj8k5rUKN7TkAqJWNNeXCKSRT/OjwkvEAk17ZZeP5KmRstEAlw5JCE1dnuyEqqSIsoT\nnpW1X7Q9KoqF8U9LX90vFos0dS9IGaJCSxOeVuSna8FNjLxdE/eYF3mzRvOqbp4Q11aRWYmy\nyLtHtRfKAAAgAElEQVSa/o7XTsoEfMikuHxEC95YWmxpUlRxfoYWLvuS3JrEyKKkqKYpA9Wg\nukwc+6gs+mFZTbmmbiIpQ+StipTImuQXWvgdNeTllx0JgiAIovsPyW/blncZwZExRJuMOvL2\nf8z/X1R17IRCIWBuLl8NxWQygYqKikbf6/n5dYLoxYtorVmoQ2mS9w7saGeiRyUIYtBvBZrU\nRJIkmi+Dba5jJ8d3wACFBaZ6/ft3B0RRUbHNy/r7+y9qhLOzs/JWWTowCAJaWRBgbseg0ggz\nW/XXsdZDY1DMbPRNrdgMhqZRhdaOdfejrYsW0p4aW7L0DGgWdlpYR2zApRsaM8w66NEZmsa0\nERRY2LPYhjRjCy38jtYuDBqDsHHVQlU2znVN6+CsaRvtXep+PDtXLURMmlrpGxgxjczUl9Gu\nx9CYZWjMNO+ghfXgbA7N0ITOMWWwOZquqiEoMLdj0uiEaYe3vYRC9ujgsUT5nxGHD79+u8b8\nN0CwOKYtw2X9f0ULG3i9N3v27Fl9bd+2IQBUXzxhZWUFlJeXA/aAtbU1kBAfD/SrL1BcXAxU\nVlZq10wdjWlJx04IIO5RSu/AD2e6GzMp9n2VUm/ncjlARWVlLdBYPkpWWVkDMLhchXWGzXXs\nSF6lAKCk7h3h+UNaZgGfbubo7R8wf816S0tmK1fBrFmzZs2aVf/v9OnT09LSlDEVQK8xRlIJ\nqXZ20cY4dNaz68iiULXz7PHsrp0cevbuxBd/MnLTZD79tbDyxMSK5T9eO0mbaQxKr/estVIV\ngC4DTLRVVceebI8ebK3o8Mz+lOHtLzWzJhw6aurYzVxOMbMGvxYjp2phbYeFrYGFrRZcMQB6\nBnSf/h20UhWVRvQdb6WVqgB0H2VMyqCJ2qJWEN08HJwD6BsZiSoqko4dfrR5l79uDVhbmASe\nL9nbuprq/xFmY749/u7k41LVsXNycSHwLDdXhq4UePbqZYijZ347vb7vdCsKALL0yu6gNMDV\n3v6fMFZHqwgrAaDjN1eOLDNTYTcPDw/gaWJiItBoXhcZycliwMvdXaFwcx273IuXcgHkpFX0\n9B/o3VNUGPfs8bmdj86f8PESArZcbUp5ydGKVydHW16ddnHwIBw8dH2JCmhLXZHOgN9g7Zx5\nOgPvzXzbTsp/G2/dqwNqLx06UwaYTPn9x4qFCy/nHj9080f/0Zom6NWh419H1ZvJbMSIbqi9\nc+sJCYAx4sNAB+Sfnu3XZ+riNeuWz/T3nnQ0HxSv2TO6/BPG6miVKjEAwshSFa8OgOOQIU5A\n8t9/Kwya5V2//groMGSIe2v71cGwcuQCMAzYcevGxTPnrt6PS3+1d4wFWfAyBmD4+nZWzRod\nOv5XKC0gC7NJmRZC7HT8W5SdPfRXNWAxfd60mYETDYGSM4f+arw4JG27H4UgqH1/yWlhb+HV\nBcYEQVgtuaewkqcm8fK2xWN7uVoZ6TFYHAvX3hNW/P4gVzEs8cVaR4IgbNeGg59w/pu5gzt1\nMGHTCKvl9+RfVybdOrpt1bQhfp6OlhwWQ49r5d5n/PJdt7IUEgPVISt5unfF2G4OJmwm29Su\ny6glu+4XyEr2DiMIgphwvNkiI2XM0xD+o3Wd6QRBdV58p8kUTk7QGFOCIAwG/5L05kZpOBVV\nL4+tm9zbxYLD0uPYdB7y/ra/s0VNam7nvCnZOrIyOnjDvKFdHc0MmHSmobmti1efMe9/vis0\nW6UyrSye4Kdf27F0TA9XCy6LoWdk7d5n0spf7+U0aUlDQ0QZV78LHOxpbaTH1Dd37TXti7NJ\n6oUik6qSeOTDyZM/OZ0l/6/yyWZ/48avzBTrUb9GC1WuVYcKlC+xAEC4byNJkiSfrHFo+qNy\nP7hFkmTUly6AfuAV0eFhNAAMJoNl5NB9yjdXMyUNdaX82JMOsJ26+XVytOSw6Cyupa0FG6B2\n2Rwtqy91yp8OwGWDIOXi19P7upgb0IkOa57UHQKgdv0svOZN2dcfWwMAa9jV2vabMm3aNACZ\nmZlaOzk6/p+orZRlJ0l41bL2i/5bxL2QrZkknuUnmuUnWjpcFHZN+rYt+i+gqkyWmyYTi96m\nDTm/DKAAsF8VLiNJ0c33zQAwAg6XNCqS93M/KgC/rcnN9q49M80QgMMnjxquRWHioWnOdAAg\nWCb2Xr7eDsYMACDMBm9/wW/Y9/kaBwAdlu3e5KcPgGlkY9fBVM9q6R351ycnAwCVZWTt3Mmv\nh29HB1N5+Jpxv62RAgUjZFlnpjtQAYBq5OTbu3c3FxMaKNYTd385BADGB4kbl1bWvBbhHw4A\nANPFt9o/s6LoLT1YAKynnSms3yhJ2jXAAIDpmMM5zU7Fom3rOjNBsG069+zdw6MuGtd08M7X\nCma1ed6UbF1l6McdmQBAMezg6dOrTw8vZ2sukwAw/awqZcj0rX4AmIFXGhlY+PfyrvIYJ5al\nR7fuvq6m8pYY9d74sLx5Q5bv3dHPCKBxbN09HE2Ycr/KePgfqao/3lR37JohLXl1cc/mT1cu\nX/Hpln1X4yrfoWfs/yiKjl1xxMWg3WONARCuK4KCgoKCgk4/ySfJzB19DQGatZMdgwAAww5u\nDmZ6BEBYvP+gwecSRgeaAQDdyL5Ttx5dXczk1xOj65ZXDY9ZuWNn3S/AlGLiMXD83A8WTJq6\nK6rOsWP3GzOYy3IcPH/NV1+v/WC4Ax0A2AGXlGmKSo4dr1pclF0r5EvaL9oeBRm81w9KkqMq\nxEJN+92MGN6toyW3j5ZkxPA0rKowQ3Rtf9m57SWPL1aJBJreSBXFouTI6qIsQftF2yM/VfDo\nQvnTkIqKYnH7pduEXyOJflgRcausMLO9vqM9wq8Kv59btXlm1ffzqp79renbZNKLmrsnSx5f\nKqsoUt+/yM+Uvd9fJPfq6j+vHv8PPhNjH9Ve3F1y6ZeS+HAlXuDa5PTPomWD+UsH8j+fLEh5\n/bb84JQtPgQA9y8iSZIkSen9j20BUPvvzmtUqOjPkXQAnTbENdm78sRYFgDXL6PqN9XcXeFO\nASj2o7+7nv7mJqx6dSjQkwUQDivv11//8n6dzmTSbMdsC83kyUiSJAVFxVXyr6NObQ++l1zZ\n8NiTVSaGfN7fCKB4ffOqkRFZvw82AMD2/fhKRt0BRTm3PuvDodPpzRw75c1rEVUcO5KUpv4x\nmAOAO2p/uowkSVIYudGPAcBm1uXixgXlp4JGo1Edpux9XedMSIse/TDUDADF87OnoqaFWzxv\nyrYubXsvAMwuH1/LbtRefm74mR1nXpLKl2nJscs5MIoLgOo0dX9UubwlkqLH20ZaAoDF9IsN\nrwzyhjBYLJb77H0vSuS/tCDp9AJ3GgDOnEsq32JacOx0/NsoOnYkSZLZn3cAQPQ+16hU1MI3\nYiXNYIw9WtVQsCT54alvZvZzM9dnMPTNnHtPXff90m4s6AUElb0pInfsQPFefiO/sVv1ZlCw\nJvbE6rG+dkYshp6RmSEFMFt0q+WONj4+/lYjBg4cqKRjV14kuHsm886pjAcXswQ8jXy7omze\n34ez5J+I28Xt79A6xdnCsz/m139KctR3L4R82emtxUHfFMk/T69Ut79P65QXiq78kXf5t9zL\nv+VmxmnU9ZYXiM5sy5d/Lv9aKBJq5KbcO134154c+aesQP3TVZwj3TyzqvGnNF99nyAjpvb8\nT3nyT8jeArFIzTYe+E7SxKub5Sf6ZoFG3nBVZXVWRg6Pp6kfTJJkbQ0vLSm7qKBUw3oyYgXH\nNxXWf3KT1P8do+5Llg7k13++nCaQvRU3OOoLVwDw/i6hboMs4nNnAOi6NalRscoTY/UAOK9/\noWBlsdzh896UWL8pbWcPKkDz+up5kx9O8mqTLxVgBRx+M2jzvG7SxWPdC+VPZP6v/gDsVz97\ns0EavtYBAKPvL+mKJfMODpevjG/s2KlgXovUOXat0mR0kCRzgyeZAWD33h4rrn7wiTsVoDgv\nD61ULPXmVFh+cEvRruKg8foA9CecqmhWuPl5U7p11z/gAui9I6ONpipTprljJ3v2qSMA2K54\noGhc1aUZJgAIny3xTRpC6fRFlMJZq700xxSA8cK/2zx0C2gWsCoTVZcV5uaUaUe3VIeSNNex\ns523sDNAcWgc++3z0RIXAPYrHje+VmQ3FnAhevbsVUNBU9d+0zcGP0wqrCgvyox9fPGX1QuW\nTPYFP/TmwzeCXq3p2L2RytPvNGvnX5FZ5aVhn7rVVsssJv2yaVjLygW//vrr8Ebcv39fyUYX\n5/BkMhKAWCgrK9ToiivJbdAlLs0VaKIYV6wYLVGU1TQMRHkqCiUiQYMpBRnqVwWgMENQrwBc\nkKaRDnPjRgl5sopC9SNwBLXSqtKG3YtzWooSUo78tKZqc3mp6uvPNWljZbGabSzIauFiys/U\nSJMwNye/vKyiML9Ik0rkFOSVVFZU52YVSiRqnquiIqxZg20bFS7Ob78QffopSkrUqTA9XuHk\nlBWSlaVaUK5WEdmDQ8dSAKLXvDkedZuIboHzvAG8OnwkqqEgZ2LgeA6QdiLoUSMrC04G3RaD\n6DVvbn1YcuaFs8+lQO+FH3VvksOY2mX2dG9AcC/0sWIIZq+Fy/xa03sRFUWFHNrx9eplHy6Y\nN3fOnDlz5qy9VEgHsiIi3pz2uOvXMwHa8A/nOyruaz37wzFNNY/UMK9FWpU74TRVO7GZeeDI\nAnvwwr+YNnbC7J+TpPSun5/cMZjTYrWdFq8cpmiX2YyVsy2A2pvXHjQNFGx+3pRvnb29PYCY\ny0ERla1edcqUaU7s1asZALovX91f0TjDcesWuwPky6vX8hR3GbBshY/CclZ2//7dAJSnpCh/\nXDnqSRBJ8x7s2/rjgYv3XuXWyoDJZ8lzUwCg6vYPK48nOM7Y8c0oFaP4dfxDUHx7dGv8IxP2\n9pZA0u/9J/QWX5oj/6bi71meo08W0KhQfNzn5pYB5g3/t6ZjV4cg5rfJAZueU7qtv3B4ZmtC\nCMOHDzc0bJBiuXz5ckJCgjINMTBqWJ1mwNVI76qx8habQ9NkWaU+V+EO0jdSX9NLn6vwlmVo\nrNEKTUMTWot/q4GBcZM2qm8YQ49CZ1LEwroew4CrvmEc06YvpVxz9V9T9bkKjdLnqNlGQyMC\naPr05xhrtHDXyJhbVlLG4SolYNQ2XCPDmqpafQM2jaZOA0+exOLFqK7G6D5Uf6+G7amZ1Nvn\nsH8/Dh7E5MkqVPgqnHx0U+F0kcDZP8npSwiOsRoGqovo5qHgHIA6OHB2Iz0Hj8DA3pvWhicd\nPfTo21/fyJ7ojZ03xeTUoeyTx+7u6DdEfv1mnDj2UApq/3mznep3fvXqFQBm8bX18xv5hXLI\n9FIAtTk5FUCD8g+na1fHFq2rCt8xc8ZX1zJbfAsqLS0FzAAgMTEJgHPXrs0uFKaPT0eciWy8\nSXXzWkYVuRPjgF+DVz0e+HPs33cAdp8tpzb2bCWbOaVz545Nt9E6dXIHinjx8VkY21j9tIXz\npnzrOn2w7r2f5117+HUPm309ho4Y1K+vf7+BA3q5Nn7IKVOmOfKfw8DLq1kIPOHl7UVBkiwh\nIQFopEfF9fBoKptlYmVFB8Q1Kms9q/Fg5UfsCBj16d2SFpxXTmdOZtDR48UDV4xa8G/elzoA\nAGRG8ILRm+9HpuaXC+hcSyv9MoDBMFC8eWg0xd9cHLl58MSTBQCcpu3dONmay2ZQCeHtjRN2\nPhUKFR4lzXXsAF7Mhb2n70ZFRb54+iKxRETCePz921v9W34NA4AJEyZMmDCh/t/09HQlHTsr\nRwOphKwqE1rYsg2NNXLs7DwMqkvFhVl8tgGts79GF6pdR1Z+Cis7QSD/264jq91dWkPfiOoz\nVP/V3VpSBjaX4jtcv/19WsfGVa9TtbQwQ8A1p7v30MgnsHFluvmxU1/yaXSiyyBDtqH6jh2F\nQvgNN45+WCniy+w6sm1c1RfdtfekunSlpb6qe31386XZualvmFt3g9JcUXGOiEojvAdwWAZq\nVjVgLOXp7aYDHQPHaTQxYmVtYWVtoUkN9ZiaG5mYcZvrFinD7t1Ytaru7zsv9Lp7Cj0cxABi\n0xj3olgAKisxZQr27sXixe3XJhFjzybZzfMygiCsTEF/c74rqimXj8lCL8s+20X16fMvCRJV\nXzp0rhRgDJ83XUGs0XF24ID14fdzgw/d3OE/uu45yhgRON360B/5Z4Nu/DokgAkg4XjQCxKM\n4YEzGvYWlpfzAQgTbx5NbO2wPB6vsefU+IW3EaVnFwSsu1ZG95i2bfPy93p5OloasZk0ChC6\nyGTon+Vicd3gsqC6WgyAw2nh4dusajXM0wb63sP6WP2cmAswBrw/v2Or3oeJpWVzkRkLS0sK\nIKuubpKwtPl5U6V1Heaee8r5cdOPhy6FP7ty6NmVQwAYFn5T127fuWawpfzGVaZMU+p+Diur\nFoY4GNbWxkBp05YYGDRXq6RQKADUmFRSde6Wf+9jOwAsp3Gbzj1PKT47Tx+Y3LA0JO+XvgBz\n4glN42l1tAE/KABvlr7KkYXNkQ+REvr2vQJmvf/hB3Mm9LdnAQDN7sOzaY0mY5M3dwJQHwMh\nujjbELCasuvWw7ii+kIJW3wA+O/Krvv/TSxdM1PkgQWgMuuyLlAmnW1Wpi3+N1bF8qql/Brt\nBH3zqqSleWKJ+J0Lt387kU9tIpOS0WGiu2cEMY/FMm2cfkGtVCrRtJ3n90vn9W4IsPvtS4lW\nbHu73LhBAgofgiDtLMW2FuIm25lM8sGDdmqTycgfPpEEdBTLP2M8xdN8RTP9hJO8RfUbJ3QR\nRz/7d6650gOjWhk5qu9yp56uaSgve7LGCYDhtDO1JEmSrz93B6A3KVghXOzcDDoA50+fke1T\ntyhyzZMWvivYM4QA0POH9CZXkejMJCoAj2+iFY74ZvGHAknfd2v0zFfVvBZRbfGEnMLzs6zq\nnRWT945mN/995aeCMvV087DUgp/7AUCPbamKhVs4b+q0TlSe8uz6sZ2fzRnoyAYAZs/vXjc1\noq0yTWPs5DYYzg9pfihh8CQKAOMP77TXEPJKIBOA31YVGkKSpOoxdjVnf9qfDW7AHw8ub5jc\n3cWs6US6dY8eHSBMTMxUsV4dGiCM3LzkVAmADgvDM9LDQ04c3H8g6OKDyx/bARQy+88ZI9fc\nbS3RZGlGRjXQNWDhsH6e9bOu+aGhSo2iAWbjd5z9bYE3Uygy8u7GAIj/SzVPPQMKS187+qp6\nhhQTa5oWdZi1hbZ0gLUIQYGXP33QVGbnPjStyNsy2RTNZasnfUjZepL2/ufUuaup3x6lfbSF\n+g5I72qERIKVK5tuJElkF9JyipqOugiFWLECbQv43Twne3i9YRCCJFHLJ6pqKUJxw8kXi7Bt\ntZRf29L+2iX3xKGbQoBmYGbZAmYGNKDm8qGzpfU7EL0D53oA1X8FXaoE+fTYiSSAM37eBIWh\nMm9vLwDpYWF5TY+nGsmJiSRg32+Ao+JVJHv2+KlinKSHhzuAtFevms3bCV+9avo815Z5ykNm\nHQ5cGFwAw6G/3j0w1hRl1z6avTu55VBPWVxcsw5IGheXBIDt6dl+9gN1Wkc3cukxau7qH4Lu\nJUVs78eA8Nn+oy/VKPOGjh09AFTHxDT3hWJjYmUAPD2bzTdrDVUfORGPHwthMm31/NYyollb\nWwN5ef/a5aIDGX8s2xwjIQCKf0BPs0a/KIMBsHr6GkqTf1m69VXLj1pLZ2d94NE6w3r5SmlW\n8IpNoQIAlffWDuxoqc/SMx51IB+QSaKXmBGE49oX9XvLqhKDN6w5HGM4cve9jd7vXtevQ8db\nwMaRGDqZMmoWxaXzO3RPCPmyl6E1d4MrnlyuKlFFg/bqVSgXLlHHy5e4fbvVb6VSnPhNKeHm\n8hJcOf6PSzwnHjn0WAZYLLicX9ACuefmmAKiW4dONFIl9p431wcQ/H3sbMG9Y8FZgNmUee8p\nhhW4T57WlQLy8e7Nd1p7qVYKJpMJoCQvT3EtVdGJH4/mKpbsNHq0PSC5dfBIluIXBScPhPCa\nVKst85RFmvTT7I//Lof5hD1BywYsOHx4dgfUPPhs5paoFteIxe7bfUcxpLDs1C8nigD28NED\n2o8f06x19I6D/K3RthvTfplOAQGOAF789tNDxSbWXNmxLxEgfANGayfhY0uo6thVVlYCDo6O\nrRaQyWSAQKDRMjwdqhB9+M+nEuhxWx5UIdzmLHQEEg/sv9/iPD0xYvmKTtSaEgCRJ77esH7x\nuK5d5j0dNLUngNjLp58JO09fvnb5KGsSENy6lKj4gpW8c+LUP+OFFBs3k8gde8IkgOzp7/Pl\n7Hyg/orH1tFkBWsTeNVSqeTfX3+nQ4cKVBaLH54vuX6g4Nm1MiFffS9HLCRvHiqPf8IrSBdl\nxAhuHSnPTVb2Br18WeXDtbFL9DOyTOkFvg+u/dN36KvDR14CcJizYHCLDgNj+IJZtoDs4eGj\njZYmuswN9Ccgvn3ow+2n8wCrGfNGNJ2r8Fj+00duVGTunTJs5fGo0oalnCQ//2XInnWzfnig\njH1dBgwwAnjnNqy6klnnIPDTLq4MWHqVz1I0mNLr488G60MUtn7yJ9ferPIW54V+OWVVqKjZ\nTIqWzFMOUcSmGV+E1RK2844cnGMNwHTsH8c/dqGIIjbP+Pxh85UBNFrJ4UWBB2Kq5b++rCR8\nx4xPLtWC4vHR+knKJKpUtnVV59bN3HD4TmJ5QwlZZezBH4MzAWqPHr7KlmkBovvHX43iAjl7\n5s89+LpuPa205OnO6YtPlgKW0zcs/ucG7FSOsXuwzAIwXXy3YQpYMcZOHDLHAHBc+0LVOWEd\nyqMQY1e6ZwgAakdbgDr9YuNidYFxf/290BhA181y1ZwmMXYkSYpzz4w3A0CjszjWnYYs2H4n\nr3S9IwDCZtnzmoaq6KY0AHBY8/zNEZ5/5tLqhTXyzxZ12CIiIs40ok+fPlAuxk4mlUXeKb51\nLDvxeUW7hdslKrQsZG/OraN5vCpN5Y5lUjLiVmXErUq1xc8ak5VQHXWnuKpUCxr8NRWimLDS\n0jwt6J+JhdKo0NK4JxVaCRdLfV358l4Jr0pTrWOSJDNiq8MuFmTG17RftD2kElnq64qSXC2c\nLpIkCzNrM+Or2i/XJjIZeeNIwaVfc+Wf59fL2t+nFeKe1AZvKWz8ubpPWTW7Xr2aBti1+xk4\nsNXazv4prQ+kU+Yj1ILAdqtI7svz5Hh887r1QpFfuACAyxeRjW7wwn0NjqDj6pajAcWpwQs6\ny4UEqIa2nfx69e7R1aND3Zr8RiHLbcXYkbLUvcPlSxgYps4+vXp3tTekAMZDfv7tA1M0jrEj\nSVKWebou8wTN2Llbnz5+riZ0UKwm/PzFEACYFKxw+yprXovUxdi1Kndi6v5ZWF3R6nsrXSkA\n1W3V/cZ9guDZl13pAGEXeK3hum7IPNGJCUK/g3evPj06WspDII0HbItS0IBv87wp1bryP4YC\nACh6Fq5devb179nVzVy+/s3Y/8cIvtJlyJYzTxT8/VEX+Ro4PStPvx7d3M3eZJ74pqXME28x\nxs6nRw86Sv8Kvtly7EPhib2XaqDft68uV+w/CGtOCEmSFQeGAUBBfj4As5EnSVJyakLjYnUi\nc2Pt7e3QMGbs+tWNXb0UqqPZ9BnkAiDgUHVlXuydQ2uHWDzKKwWMZu/Z1l2/oarKE/PNFXZE\n9x9SmlyC1PocK38vbL7EB8DBgwenNeLJkydKNrqmQlKYwZeIyfSYKg3H7UgZmZfMAyDky4qy\nNB1cLskRpb/mpb/mFWZoOkZJkkh6UVGUzc+Mq26/dHtkxdfkptQmvqjQvKrCTEFeCi89urqy\nRCN1PQBioSw5srIgg5eTrIX4qaSIqqpScdKLyvaLtkdZgSD1ZWXs49L2i7YHKSNjHpUmPi+v\nKdco66agVsqvbhgkL81X/+RXFTdV/6oqlSh5HxUXq3y4NnapLFOtqqpylY+uPH8fDs4HCL/5\ngd6tF/KdP78rgNRjhx40DJlaTA8cVbcE3nPOvB4tTrnTnGceiogP3bt25pDOxoLsmMiXSQVC\njqv/xCWbD15/umOkUiYSzov/enr+q+m9XTi87LiY5DLjPgu2XY/6e2Xn5iOMhP204Bdhez4O\n8LEm82JeJhSw/AJ/vBVxboIJD4ABh6PQ32vDPFJQVdoKNfJrv+zq0jm7U2QM3y9PbhvQuE9g\n9th46ru+bDL76PyFwQWK1RoO+PFJ+NHVIzrUpEW/Sq816jho/vdXo25+6qP8MnqlWmc4bsuJ\nnz7/YExvFwN+buyLp1HJJSyX/tNW/34/5u66biyly7SC5cjfnrwO+XFxgJ+VJDv6ZWw+xb7X\nhI93h0bf39jPSOmWqIOqcieGkxZOW3P1xMFFc3wvHFnarfGoqCTv1oZJK0JqYPPRhwH/lzH0\nbwWSJAG0r2DQUCL/fiyAp48kqNOxa7YlNSqqGhjcv7+Cb6bXr58fDvytmbnjx4+X6z3KCQ4O\nfv36tTI7sjk0AyN6TYXYwk5Pw0B+gkIYWzLKCkQUKmFspZFyCgBja7qpDQMgzTpoWhVBwNbd\noDibb+XYlmCgklg5satKRbYeLTrYqmFqw+SY0hl6VEMTTe9sOpNi48yuKhNb2KuvdVJPB1d2\nTmJtB1ctnC4jc6aVI9vYUn3BmnoICuHkzRXUSvSNNDpdTDaFzqCIRXXuhCZ6hM3VB/U5VCXv\nI2PVFYHa2MWgdS0krZRXiYDDJeThdku5ffWS/KrpRm7gFX5g+0dg2g9evH3w4u1tlem+I4Pc\n0cb3LNdJm09N2txkq8PeEnJvs7IUs95LfwlZ+kvjbeSNhCQAzs7OzYorY17LNs0PIecrU9Ak\nICibDGrxK1rHdY9q17WyH8dn3o4L89o6Le2et/ZbR7XpPeuT3rM+aasSZcoAcFz/glzffDPb\nOWDd3oDWGllH6w0Zc0RAHmnnyC2h8pOCM+HHPVPvzTx7aVkvp597D7ItFgHxpz5beirs2t5p\n9AkAACAASURBVLXHWXwQju/v/3aQpj2cDqWxtrYGEoozM6tLmBd3/37yWr2OnaO3/8ipS1a9\nz8/KflNOSaqqqgCapWUTESN9S0tFbTWyJuPR1QsXLl178DIpLS1XCODOzrUHbNe/39uslbHg\nESNGjBgxov7fyMhIJR07Ko3wn2glqJXoGWgktyunZ4BZSa7Q0JjWWKxYPWh0YtAMrck9efQw\n8uihnZc5Y0tmr4CmipfqwdKn9puknaoAePdvNdmdqnTqY+TZ20grK3ZpDIp3f63pqjt5acEf\noVCIbsONou5UiAQyA2Oa9wBlwotaxrkrK/EZr3Fqk469lPWGXV0REaHa4dzcWv3KwU2FX8uy\nA1hacNr/v6m4dOhCGWA5cKBH+4V1/E+gRq9mM/34Q6rVrCV7wpPCLiYBQNz5H+MAgGLS86MD\nZ38K0K6ooY42MenXzxN3429/39M1NqGS0LfvOShgsI2eqDjp6b0zO+6e3LPdW78cMPP3b/2u\nNvNxwqXoTl3eXA0cDgfILCwsUxSorC0srK1TOZeTe2BO/08egWHq3s1vYE/KX2GZstLwnR/2\nPXnlYNjFBU7aVnkgCGjFqwNApRGWDloYm9Hx1nkHdVi0iJUTa9T7VkK+lKWvUSYSNoc6dK7x\n63u1ZflilgHFzU/PRelprYAAnD6t2uECWk8k6utP6OlDSR2TviP+y6Vi/mUyL++4yp44d6iL\nYd15E2Td3Bq46EwZ6D7Ll/TXncz/F9TqJhlOU355MvqTexcu3Hj8KjW/XEA1MHfw7jtqytQR\n7v/kuLmOlugyf37n7z6LjU2gWI3bffng8gbFk+rYoyvGLTwSzQPs5n44sPUOkM5lA2gQ8Hbx\n8TFE9MuwsJpF4xom8gRhYU3e2xl2Q1bt2bBs1lA3LhUh81lhRyWjFo2O2B/y1/K1pyedn6n+\nAIMOHTrkEBRo6NXJMbKgDZimzi05aRI++wz5+cqWd3DAmDGtfstkYdL7lBO/tr/Cl6WHiQt0\nvogqVEcd+GjTulUcGycX5w5GsrLU6JisaikoViN/OfFZp//pVyAdjVHGsRPzKmpFFKYBR69x\naX2nQXPXDJr7TxmmQ2kolPobVjHUjkDDN2jrpm4aY0cdOW+WRdC+4GX9YtfmJ2RVMcw9+k6Y\n4vTkSDGA3PvxQHcAgMXkb3c1qYozfNcnESGfR9y//xwzlcwhqEOHjncXfX1s3Yr585Utv307\nWG2Ohk9ZSIl4SCa8bGftxrKNVBPztovoUMRu3Odf5Z2/E/Y6PTMqI1pM51h6DhoTMHvlJ/N7\nWWpnrkPHfwXK/NiX5xlPPW+6+G7J3kENG3PDzz3JYTgNGOennSyGOtQl+vDhGBkMO7kTcX+t\n6OWws9fgfp1t9ETFSeF3HyVXSPWcvIzTY7KD9t/f+ftgZV/ZmMNWf+h28LvkV5E0YzefHlaU\noqf7vr6uZ2lEFFYozn1lXfh8w1/5AJATJgbIp79/lZkHgP/8UQaGOWq7sTp06NAEmZRUI7tG\nYCCePsUff7RfcvVqTJ3aThk6Axv2UJeMkVaVtezbkcDURZQh43RDTCrC7Ra4eX9g02UW/0W0\nux5Ch1Ko7cU/2TF16nnuB7fqRDd0vC3KwsLiAOqwL1/sdb3wy+/BVx88/SuqQkg3tHT0mbpm\n6pJV7ws22Yw6UPLoUSIGK6uIKLyz60CyhGrt3YVdkPj6eZG5u/+Hm+yfbN4bBVAYjVdQlEVe\nPNo403LGvdMZAMDLrSgBHJvVHBYWFhcXV/9vWlqa8k1NeFqVn8Z39TW066hpQHVBhiA+vNLE\nmtFlgLHmQVqZsdUk4Ni5xSTeqlGYyS/KErj7cZhsTWff+DXS9OhqG1e2kbmmi5lIEonPK9mG\nVHtPLayxzUvhVRSJPHpyNc+cVl4oyoipdvQ2NLbQtI1SCZkcWWlswbR01MJy3dzkWn6t1NVH\nC6EpMQ8rirIErr6G9p302y/dJknPqxOf1xhZ0PuMM6UxVDv5v/2Gx/fwKr6tMj19yR07lKqW\nY4waMVEjAJtJNppXAAmIJagVEgx9nVenQ4ea6IZn/9up07Gztze06Bm4pWfglmYl4u3tgPK8\nvDygIwBYD+yMS097+Tf89k23SG8eO1EIozl/PA4a39CR8/649OeyKKno0aQJx8WX6qRSfKZM\ncfnuu4LAKzVHxgC85xsHDdz03HBS8KvzM61aMvfkyZN79uxRo52kjEx9WU2SSHtdo7ljlxlb\nU1spqa2UuPkaargwViyUxT+tAGDtxNbcG0t6UVlTIdHn0py7aOom5ibXZsbV8Kol3Udoutiz\nskSUHl0NwMZVn0bXtMeND68QCWTGVkxrZ01dqPTo6oIMvkwGv+GarrQtyxdkxFTns3maO3ak\njIx7XC6Vkpb2ehoKxEhEsoyYWgDp0bWaO3YZMTyZlCzLF1UUicxsmSrtS6HAuQOZm4pqCSFs\nFiDHpMCQRjrZqLCWpaIUQhEhEBE0KkmhEhSQMpIQS+vyzJaXqGSdDh06GnhXQlPLrgTaEARB\nEB2/ap5UtzziyKdT+rhbGjIZbBN7n1FLf75b0ERuU5p08dtVc0b39nSwMmYz2Sa2Hr5D5m46\n/apMIQcWWZMRdvqn1TOHdfe0N2Ez9Lg2nv2mrj0QXtJmIG+rtil3UAAgq+Iubg0c6utua8zW\n41o7e/Wbuv7IE8VGCI6PIQjCaGFLWRbDV9kSBDFo75uHXaOGDN2eAKA4aFlLDZEmXfx21adB\nKQBK/hxZZ+GuqKaJA4UvEgFcnksnCIIgCCpr8olqgFaYk1BeP1XCS9x/LqHllM1vGhDz2+SA\nTc8p3dZfONyyVwdg5syZ+xrRvXv3tqpsBEEhHL0MWPpURy9NuzcAdh76LDbVxkVPz1DTdxs6\nk+Lux3X342ru1QFw9eFYO7NtXLSg8WDjwu7gxtbcQQTANWXYexp07MnV3KsD4N6da+uub26n\nmmPRIg6dDcztWE5eWhhHNLFi2XU00IrWDEEhPHoaOXfhaC77R2NQ7DqyGXoUh05auCTsOuoR\nFHDM6FwLdQwzMgadAhMGackkjRkkl05y6aQxg7RkkiYMkk6BsSqCCFxjQD5EJyWEIvBFhFBc\n59UBMNKaJI4OHf9/KJGd4uxkKKQRa9hYl9VKY4rOT7WEgYEBAI8voxS/K7g434UOECadR89e\nunzRzMGuBgBhM+FIeuP0KPygABBsq449BowYN2XqxFEDOpnTAVBsJhzPaMj2kr3LHwAYpu69\nR0yYOvm9AZ5mNACEzbhDaa3lSmrDNuUOSpIVN5a50wGC23HknMUrVy6dO9rLmAIQ5uOOpCvW\n1topfbKyA4CBfxQ3b8jgrhYAwKC21BB+UAAIph4VAKfzqHoLAWD4sYaMTimzjQBQbAIWL168\nePGi90e51sU+Exzvaes3b1y3dFZ/ByYAJhWwmvFnXFHDIeoSl52N2DHUFDDw+/S+KnmPpk2b\nBuVSiunQoUNzxEL1E9/98TNpzZK18Tn0hwq1bVwh62kjbe2TEN1+DTp06GiRd8GxKwiaYAbr\n2Xu+9m/uPNVcCTQF4DDvr/w3OT0FqX+8ZwLojz6Y21BOVpqdUamQe1KYeXq2AwCzD2/UZwMt\nPPf1qj03kioa0oNWx+4dYwGAPSm4xQykbdmm5EHJ1B+7ATCbEJzb8EgtvDTXBoDdJ0/rN6ni\n2DVuyKuvPQEYj1/2XvOGyEqz00JXOgIwWxYqq7NwojEAOHzakINR7tjRB/5d93/iJm8AHBYB\ngMqg0xhsE0ffUYu+WzsICrliSbLOsWN19eQC3D5fP1Yxj6vOsdOh47+F0hLSw7JVr87LVlZZ\n3n4l9aQnkf2dW/bq1i7QQtplHTr+b3n7U7HZhz/4+BJ9/p+/jm1pGP/+hQulwMC128ZavZnn\nYjov2fqRO2qv/3Yktb4cYWLroBgqxbCf9uFYM6AkObk+WabF5G93LR3hxm2YMjPotHjXJ34A\n7/7956rapuRBkZ6WBqDnuAk2DdNYFmMn+NOAEjXSMDZtSJf5C3tSUX79qeesbk0bQphIb287\nlAF4LKzTsWPYT5vlRQNQW9h6DlEXHx9DgOjkCoCcGCwU1pamR17f7VcRCyBzZ48JxxtNIvP4\ngOBVPG3Q1tCb3/bhArL8qyt89Qmaw6T9cZomYtWhQ8e7gokpfj1EMFqaQmeysOcowVFlHtvR\nDd/tJfSbRQp064NvdutWTujQoT5KBxjVPvxpyZJTDf+nRQHgP9q9ZMm5Fkp3W7x3ka8StZIZ\n+xesvGqwIOTnAOPqn5t/zysoqAbYLi6KIVuuri5AUtSd0PIvXFpNSlhx//ydEqBD165tR2tw\nuVwATGbTx1V7til90I6dO1Px6HnIlYL506zqHlgl1/56LIHRmFG9lay4DZyX/fbFif6bI34+\naqbYkJrYoBWTP75RTXX9eM96H8obC68lSQBw7Fs/LXU6di9zAdDo8slbQcz2DceauqGyvEub\ng/IBwmbRvWvrvfQAQcKfc0YtPV/s9dHFa7+MtXn7Lw46dOjQGsPfw+VQYvPn5JOHIEmABEFB\n/yH4Zivh6a1ybf2HE2ceEJeDyegXqKkibeyJwaMxcDRB0T03dOjQAKUdO0HclX1xTTeKEkL2\nJbRUevIwZRw7WeruwDV3jN6/sSuAC1S3UELPzIwN8NLTi4BGennp6ekAkJiYCCh4RnFHV/3y\nRCATVBalvbj7KKXKoMvHB7/s15YNZNqRYw8Bi7Fje6lom9IH7bBw56bgUV9dmOnpdWTsQA9T\noiw5LORGCjdgU/Cfs5t6V7x7P8yZc6TpIUoiytswgNVjY8jF2tGTfnolBVF964c5C4830rHr\ntPDkLp+/PltypsFCKiB1d2+jRuawb38acXLOzSoQ+mk3Nm54lP/s4slHViMGcULuVTUUS945\nceqFEhKgMlN3LJ0PYdHL0NBXRYS139DOTlzTf+DpLBKSDKYW3uYrK3H1Kjp1go+P5pVph8JM\nWWacpKqMFAtJfS5hYklx8aHpGeiGLnS8W3TthnM3iOIipCYBgFtHmGqw6trMAh+skl/kuktd\nhw7toIxjZ909IEDFKbXuSiScl8bvnPf5A+PFN3eNaDXPDTFwTIBh0Nl7P319e8beYSYEAEhy\nj234PQEAysubujtZdw/sO1qXhZBmO+rboCNfDmpLu5z3fNOMb8LFFpN+3jissQ6WMrYpf1BW\nry/vhjuvnL5k3/WguOsAALbHhGWzJ3Rr/kAUp945kdpsa3tQuGaGdAD69t72/Od/Hb/VSMfu\ng4G2d+cvaGThoNGG967HN59PkSb/umTJRQDimsK0iLv3q0CwjM3w8uD2WHN3/8m/PNrI3WwR\n0niPytJS+ZysNP3O0fSG7fkRV4PNJuxbM6D5QdTWsZNJEbSFnxkn7T6C/t4HGi2olErRty/k\nVoSGYvBgTSoDgKykMgD27uokSSZJxD4WP7wgKi+UATCzEXHNJPHhLAGPQlDg7kcbNJVpqtbI\nZ2acMPp+raMX06u/puuIK4qkYeeqWfqUgTMM6Zo51lIJee9kTWWx1H+SgaWj+kuSSRkSXpHJ\nEbyaIoGhhZ5bdz2PLgShwbuEVCJLjS7lmrEs7bSwjjgnuVLAl7h6m2rurpTk8fNSa1y6GOlz\nNV1jK+BJUl+Vm9uyLew0vSRMzcisl+UEBSamWsgNnvi8ujBd6DOEyzHTtI3Kc/8+Fi3UWm0H\nDqF/f63VpkOHJijzYPVfHxLSfikVEUdvm/P1E+slN3cMb0vDkzvlx5/HPlh4Zf+oThETxg1w\nZlfG3b5wNdXW27U4OoVKbaovMepIDXmEFFcXZsXeP/7tZ98O9Xmw4+rlT7q1qBTQqjyHkrYp\nfdDyB5smTd4U22ndiadLR3hZUEsS7h76fMW3s/r8FX0j/Pt+CqpZLWs+h6+y7bM7tzUD5A15\nQe22/sbdrf4tmNzEwi03rIb9tGFSw2/fYZQ/TlyV5V3dt69hJ8J6/MEHFxa41veV5M2RIYoq\nM91/SCFnfOXq+11u7/GDMq/8Xev32YWQrUMt2ujL1NaxqyyVpcdIAbx+KNHQsSssRL1vefeu\n+o4dSaIkR5yfJqiqLgdQnk+3cWaZ2dKVl/Li15AXfuFnxjXIyFjaCWkM0thCnJ/BJGVIfC5J\niZIMncXsPkJlAd6USH5lsST+iVRzxy4nQVSaJwFQmiuxctao660slmbFiUggPVqonmMn4OPS\nEdmV47KKUowdyzc0lOUk8PbuYBiZYtw8yoRACrPNfFatGlYiKMyqLi/iae7YyWRkWmwZAEt7\nA0MjTVVdshOqygoEbAOaq2+rcSdKUpLLK8qura0Uae7YVRaJ89P4AJy7iIw0U4cmSSRH1EhE\nZFYC36vfv+fYiXgoztBmbTp0vCO8JYFiMnbr3I1RNktCtw9rR4GK4vj+hUjHX7/dfuz6naDf\nrtDM3P1n7T28qHK5z2ewsGgxnRlBN7Ry6T39m8teRHevb9Yt2DlKvnBUgdrIneNHrL0j9Pv0\n2i1FZ0h525Q7aO3Nz6ZvvIeZ569smyQ/jn23SRsvmRR4DN7349p9i8NXOSh/GEXEuXf2fffd\nzmP3M2plBM0w59TCoS98+w4cNGnewoH2TQcv2j0tdT4lKa4pSnx4aM2CLy8vGbPa4enPQ7gA\nwEvcveVBs4FbXsydp2WA8EXIDYkMeL799wc/DJ3ShskffPDBoEGD6v/dtWvXkydPlGmrkTnF\nux8tOVLaO0DTR7+1NXr3Rng4mEwEBKhZSX6aKOpWTWWJBICBGRNAdgk/LozPNad1G2Zg5dx+\nV8erIo99yysrUNAezM9gGRpLSgsa2iiV4OYxYXU5OXi6ai6CZ2+2VEI6dtbIsSjJlT2/Kc6I\nkVIIKinDlT9Fbt3InqPobEOVR6JIEsmR4qQICYVKk8lkWfEklS7q3JfO5qhQVWYKuXmZLD+r\nTl8xJlbPzVWYlMwEUFGKY7tkty+Q3/xBsXVW2Twjcz1bNyOOiRbU9SgUwt3XTMiXau7VAXDy\nMtIzqLV118I4ooWdPq9abGajBUk8I0uGQyd9CpXQ0KsDQBDo7M8pzBA6emnBMOWhUsCmt5Ov\nVpXadFPJOt4VCJLU2pWtApJTE+gzL7f+PfeD6xUHRrX6dXXwOLPZV6gzLlWeHN9WL/94hY3/\nr/lD9pfd+VDhXbfy0cb3AjY9Rp+vr1//tk+TyVYNbWt20IcrOwz4JW/E/rIbCkZIz0zTm36W\nmHOJHzSeAgCC42P05l5ta8Ru4B/F95bUz94KX24bNnh9WAUAqnGnkWN7G1VmpSdFR8YXCgMO\n80Pmtz5s0ey0tHTo29M5o85WS/W7zFs9ybI4Kfza+YeZQqNuQ8wjQ5PHB73JPJHxQyenz+MB\nuokrtyalRATjMXeSrgxROuZm+vTpZ86cyczMtLe3V6Y8Saogbd8GQiHCwuDmBuUO25T4J7yX\noTVtFPAZYuDZp61eSibFie952YltSj4rMnYxy7u/Uk5tfqowOaK2JFskl3s1tqI7ddFz8mar\nNFNJkrh7WvToskjazEamHjFmEdPbX4XXwtI8WchefnFO07oYLGLAVKbPYKWcg5w0cvUMaW1V\nO8UMufjpDNXGQdfR6miLezfxwRStdX+HLxADdOk1dbwbvKURO4rL8A8+aNL782JDToYXcn0m\nTvEzYfe3a31nMmX/79dFMAucPbLtbq46NbUIAJ2u0MqSW6tHTNgVpTdo680r67s1H5TTyLYW\nDioSiQAUFRUBjR278sJCMaDPZKoZFpS9f9kXYRUAOP7f3/378zcNkVWlPLgUb9LW79ryaWmK\n+9zlgx7vuJPz+vh3sTQm18Zj8KLln3w5JW6aU2ijUmbjV8/6/cPg8llHk6ecZo49LioPGTP4\no4u3fxtp+Y90q1rx6gAwmRg6VM19014L2vbqALwMrWHpU5y6tOpdv7wnVsmrA3DruNCtG43V\nZg5NmQwRNyozY/iNN5YXiMsLxFlxgr4TjBh6yl5vIfuFEXfELX4l5JPndwtEAqbfUKUczeJs\n6akfeEJ+C52oSEDeDhLUVpD+E9sZ3BKL8O0yWbteHYDqSmz5SPbLJSpNlzHxnacgQxL7kF+U\nJZGISANjqkNnulc/PYbev+GUUwi5rrt20NajSYcOzXlbjl2Pjw70aLIt5+d+J8MLrQI2HNjS\neKUiPzupxNTNjl132wjTL62d9PVjicGgzRsC6rvN0vDzD/UGjOlqXt8eaWnU3oXrr0nBGBAw\nrH4SQ5Z3acmwGX8mGI3cffviCq8Wc0IqbZuSB+3ev7/e3osvf/v6VOCJGbbyjlBaeGX9zocA\ne9iwPu2frRaQ5f22O1wGML1/fHRrXaOGUDiug+a51v1TfGSi94JLVWOP5v01z0jRQqrejQWW\nY+m5V2YbA6/P3QXAz5JkX9/82ZYjN1/m1DKsvYbN/36TZNEX95njgtIuTDMBcn7ubffJUwU7\nDDy7O73pkKkEQOnux43YM36g8Ezo/nHvsNgJv0ZaXSZm6lE5pnSVxrGEPFnkzTYXSb8h4ma1\njSuDyW6hdpkUYReFKhwVACCoJZ9dFw2Y0pYD9Cq0qolXV09JjujxpYqB002Uae/rh5LWvLp6\nrh8S2rlTLezaqU4ixqVf+S16dfU8uSK0caU6ebf1OLoaLMvNUHZ8JTOFvH5aNnb2u3sF/lcj\n4kvTY6orS0QEAa4Zw8mbQ1frBfVlKP/F3w2xaUK+pDRPkvRcOPpDDtdcez5XKxAESadpbcSO\nQkC3sFfHO8K7/0pbeGKW85bCLn6dnSwNpYXxT57ElojZXVaeO7WkURhN+b2tEz+faeLcycPJ\nzsaYWlWQERvxKo8PivV7v+1bavumWPLOiVP/jJdQOriZRO5YOl/hON7vt7iKsw2UPCh3+vc/\nHLi/8u7ZmR0j948Z7GVJKYl/cPVWQhVMR+zcNq39VbctkLxz4s5UEgCdeNxGQyoLUgsBXFnW\nrd/ZbtaNLDS11y/NogcuntJ4DFGWtrnH+LQOI4dNe59V9PTKpXOb5kdMm+SIcxe/3vZs0rae\nylwrhMu6+x+dHfrBwSkDhMGhR6bYa+3pLBZKc1OrBLUSA2OmjZMhharmM5QkEf2gIjO2bpEw\nx5TuO8yYY6ps3N5/2Dvv8CiqNQ5/Z7b3zWbTey8QSEgCoYXepFoBQcFyrahYsBfAhop69YqK\nooAiiiCggvQOEkoKPZRAei+bbJ96/9iQbOqWWRBw3ofnITs7c+bM7Myc33znKxeOmwmrU4MB\nYWUuHDcnZXbipV58njLoGGBcHgjOHCa7EXYNlURBhzrA9tSW4oWnzRG9HBS5ZxjY/QvusDMk\nAXvX4vc85yBU4cRevLH7YswAALBvrSUiqTun1s0/uzYGb17NTJzh0hYew6THq8sMDM1o/GQq\nb7dCOW5gdDV4zs4aEm/+TRuqrGWXjKmjfJTerjnbleTj9qquBYOO3vmD/vZn1dc6mx1CwPeg\nxc5jLXFwsOXGF3aazNmPjPhp7/Gj2w8bkSowbtSjLz718lNjw9s8LgMnv/Fh7bode4+cO7Ev\nu8HCk3uHJI176LaZc56enuzVesc1p+egyw7+vPJgu/2MGfSFi8LOyZ0CL/7prXnxSxb975ft\nRzf/sN8MEk1I4sQn7p37ypPDg917djXW1dmm8QwnN6482eWBBE5++619T769taw0d09ZFn61\nh3fH5c19cWPIc4+Oa3O8ZGHDfw6dW9hPjQCArlx1V/x9G35veni4dNnu/7264pmdzmUG4MXO\nXrNfNGv4/aumZVpX7v5pBrsgShuElTq+swy3UABQVWyoKTUkZwYgt7yVL2XrW1QdADTWEce3\n1g+Z6svjO9Va2QUXLG2lF6ydCrvC0ySAO0NBQxXdWEurtJ1fNVdOdm6ra7uOyaGwK71I6Woc\nSzEAuJBNOswsmJ/lwPJno7aUri2jtUGdH1pZIVNe5JqwKylgKksY/xBnz3J1qb6qtEkg5IXH\ne4ul7l+0jXXm01mVDM0AQFlBY1SSNiDcmeD67iAJii/wgAYxNFlrK/RSudA3UOm2EjlzqL5F\n1dkgrPSZvxv6T/RzqZ2Te7tMotVQRZWcw8N6sA3L6B4MQOA57chNxXLcONxAwi547kFmbsfF\nygFzvv59joNtpQmT5y2ePM/RLtIWXWIWeaxvTu4UAEAYMvrZJaOf7XYd8cxNzMwuvsv4bylj\nX/wibdElZhF+Yc28h59feqDMJjUE6vBeGUPH3vPQbS1yTZowef56fkHwhFWSBw4W/W+gbWio\nXjYypAmSnn+k/9WhQtgzAH4vCH3yu7dsqg4AMP8Zj90xZ8PyE6IFRmaXbVkpAAC0Rk4AAEDy\nO5eYdwAANrWUIOFFTF91ZfqqTo9k+/btubm5LR/z8ztNcN2e8st6m6qz0VRnra8yewe4E0NX\nerGNkQABGBvJmhKrf4RTlpXGWhcc45q6WLmpzv0JoKY6RtVFbEpdhWMzW0MlQdPQvS2kqsgp\nVQcAJAG1ZUxgNyGoDFSXOHvGqouoroRdRbGTbbShvBj8u3WIbUGvs1w6VW37G7eQvQYEd79+\nNxSf19lUnY2i8w1shB1DM6ePlRoarX7BqsjE7nJyOoSwUmeOlFEUDQA0xfiHujNZYGwkjI0d\nlTqjr8fNBlIid3ZAYRioKupO8VdeIa61sPOwxY4Tdhw3DDeQsONwEWHs1M/237Xg/MEduw8e\nzc7Lztr399YV2VtXfL5k3vodH45snmWVjHtidsSqT35cuvmDgZOkAHBp+dLdOG/YYw/HtW0O\nS0nv03I55L0enfJusbqzJNDs+P33393IY2cxkQ6XOImpqROdYTU5JT4okqEpFzQZTTEkwfAF\n7R/5FpP7ws5i7HJbwuK4WYYBwkqLug2h6GYXrq5MEAzl9A/VzWkxOuXW2B5Do7Nrmgytmtik\nd6yPu8FqbqNXSJwiCZrvrmkIt5KGRisA1NcYIoGVsDMZcZuqAwBbm25AWDsV/cj2kVYgZQAA\nIABJREFUlcTpBFEkztDd3nNWFveIkyAEPMxje0HOmUAZQ+GhzevXb/xrf96Fy0WVZoE2PGng\n+NnPv/xgRheGeA4Ol+GE3U0OTx035O64IXcDADBNp39+Ydqsb7M/GqXZ+7X+6KNyAACs/+OP\nJn/68tqla/47wHqHz+P7eACyKY/ODGzXkkTdPukWwgCojsku7DGdXv/1mj25uTk5OTnnrABw\nOAuguzx2Tz311O23397y8Z133tm3b5/Do5Sr27+7y1Vuvs0rNPzGmvamApnaqRuBx0d8ISJx\nZwcDvgB1VHUAIHMlc1v7bVVdbiuWYZ3KVnswHhKKHQwg3ezC1ZUFQiQQISe9ErtJaKdyKzWv\nuvsq0fbtayQYD9lUu9qHVTY1mVJk/9YhlgncVnUAIJII/ENUujpTYJiaTa8AQK4UiSQCm+70\n9nczQbFY1vmdglCXX3WKQIQEQkR0fStJVddc5iAA3nWfii1bNnPws4dA6B3bJ3VIUl+86uzR\nv9d9fOi3n//87uCGByI4bcfhCThhdwuBlD3v/fqTn34c85cF6uzqVEQ/+PjItx7duvSHktkM\nAFCgnvbo7WzdfmxUb3rv+Xeyga8MTvAWV5Q59vGKj4+Pj49v+fjtt986s5uACEVNqbGxttkp\nJyBSodK66ZMelazI2VFvv0QbJPIOdNa7UuPPry52ymkMADSBnbtqqX3dfH4jBGqfLrf1CRXW\nVzjom0+o0OEIFBLr7ASVRI58upg8bSEohtfsU9g9CIJiutxvaDRCGDDOThEDACAMQqOdVahi\nqaBnv6Cacr1QxPcPZXVvRCRqDDqr1UICAI+PRfdiUUjV1mACK0NdCzw+1ntASGOdSSIXSuVu\nvheJZTxNgLi+or17nDZI4vCFoR3BcYIrp7o0jgbHXdt5WPiHpmKFIcPnfvnmE/eOiFE179tw\ndun0YY9t+mPOC2vu+G26W8F0HBxt4V4QbjEwgS0IoM0Y6DPjibuU9JFvVhXUAAAobnvU9QJV\nnaOdvHj7sYs1Bl3JyYfamwA9CIah5MyAngP9opO9U4YGxqa4P1gGxUiSh3uJ5TwAwHgoJF6a\nOkbjvH9MaKILgjI0oXO9GJ3s5gtVQCSvG7NWVLLUYQhIbKpjc5Q2CAvuWmPZsFlakgbxMUdD\no5NJlcMT+QqvLh9HGl+ITXLNzJmQjJy32AGAXCWKSNAGRap5fFZPRbFM0Gd4SEK6X3yqb9rw\nELXWQajK9YQvwLz95W6rOhs9B2kUmja/qUorTBzgsk01ZaS0U3s2AIQmCP1Z1BF2EoSAh3ns\nn5NXp++dCz99fHSLqgMAeeKjnz6bCmDat+/YNTpSjn8bnLC7Wcla8sziDbnVbd54mcbjHy7Y\nbQYA8Aqy/0I28fH7g+HcD8suA4Cgx6T0q7973uvRCMnfvMgA4PtejPZVCLHgF7LsNy1aMSk1\nVCMVy3zi7lxd0b4X8oSho9KitezqwjsHAm9/aVCUUunNtkxTSLx01P3+Yx8KuO0/gcnDvVyy\nNEQli2Uqp17zZSpeVHLnKtAvDPPtUPLNGboXSVIlr9ew7gpPRfSS+kU4dfZG3+dg7EcAUgXK\nvNOxRIhLEwQ7MgHyhTB0qgPFfOdDrp0xV9f3IDwe8vaXaQPlAtE1T8Z2/RFLeRkT/Htleocl\nKsJ7KHoP8e57m59I4vKRagJ4I2bKO+YiDooRDJvuQjVHNmCI8dQ/NsETKpUKAEQiDxSg4+AA\nbir25qX22HfzVn7+siI0uW9aQrhWQugqLh3fc/iykUEYMLRPWwXAG/jEI72/ePOEFQAkCUFt\nm2KqTlUCkA28npOmZhqbgq+OsIwVgDp22HDffU/ehiqOrP9pRzEAVLTxSC9e/8qbf1QAAORV\nAwDUbZ09uxYAQDtu/uKp4dfgwD2FeylVMR4acLty9yodRXbnN8bjowG3K7tJtjfsHtGaxY5n\nru3x8sOShzqwfkUlSwHg5B59x+7FpEp7DXV2kjE0njf+YdHmZV262AvFaOoLYrkz3ngIJj0h\nXfOhsa6885lUvgDGPSTROsr8M2AU6jMQ5Rxyyl0vfSjKGMGFKV4rEAL/CKl/BNvSriEJwnte\n9LqYbakqJAmcUXjxwnoIQ+IE1ycp3I0SFctcXvHDAQDfiRP7eaw3HP9uOGF3szLivb2/D/hr\ny7bdR89mbztaUW/hK3yCe457aHxy4+L31nUsvJTw4AMZb87NAgBx+8ex6Wi+EEAy+f2NKyc0\nL8oDACCMAGjYZ7uXTwMAgAV3jfUdt82Y98tW05MTrrZRn7Nh5crzrW0Zz6xceQYAIEw75xoI\nO5pmMA8V226sIWQqPl/ocmvaIMHgu1V/b2jEu4hCFYrRwNtV2qDuRFhUMj95qCBvr7PuenwB\nTHxMzHPifo1KlgZEiS7nmaoKcVMTJZJgPqHCiF4Sta9rudnSRwsUXuiv760dk7MERGBTnhD7\nhTmrjKVKNOM12Z5fLGcOEXRbdecbyht5nzgwyvEAixC89CnvxXupoksOtF1EHJr30S1oKrvR\nIHEGEHQ1neokYhlKypSE9SD1daR/hIjHrjWXkMpgzoLWa7iuGtZ85YIX57QnMI2d92OHx6qT\nmI4tmPZWFuF7x3/nj7zmboUc/xI4YXezIglMm/RI2qRH3mz/xc7HPn6vk/UtJ09eABAC4B2f\nnNr7NhatHNfxwaSeuqHklylXP0mjB/rCtit41so/zROmNnsOJb+Tb0tjB5tmiyeuJKeuJX/p\nLip248aNWVmtc70nT57sZuV2nNhbV11kjkpRRvZiG/qRva2h9IJZIMSGzfCRyF0WAQGRwnH/\n0ZzcZyw6Y7VPgILxUFgPUa8hMqnScZtjZov1OqYgz3FgAV8A4x8RO/R7a0Gq4PUYpCjJrzUb\nGAKnB2fIJXJ3zJPx6fyo3vxzR8j9a02GRkAIfEKwwXdIopN5rtonhBI05gFJ/0mi/WtNxWdI\nmgGJDI15UB4U60JTciV89DPv45eoI7u71HYDRqHnFvEkrgd9Wk3k6awqtY8kKknj8sYduHym\n1mIiElL93UujbU/5labyy40xvX3cDhhqQd9gzT9e4xsiD4tnG2NbW2Y9+lcdIMiYoNX4s1Ik\numpi1491AOAbJhx8lwdOvpNYTPD1wjZR5C79Vr9+1WbbN75yYzC1nP7izvELjmF9Xl6/fLq/\n69tzcHQKJ+z+JZQu+3B1PfiHQ2Vhxy+TBwzo9HUzJTPTztcFv3ClHgCAzM09A1PTmpfmvR6d\n8m7lrD8N3cm5Vnbs2OFGHjsbNcVmmmZqSizshV19JQ4ABE7r60g3hB0ASJW8jInK1DHM0c26\nqkIrAPiFifpOUAucNgHy+HDPc5I9v1qPbsG7yeml0KApT0pC4lzrJIkz+nrK9kdTHSlx119e\nIIReg/mndhMKJQMAfmGCmBT3jWFKb0ypYeTq5sIbfuGYqwJRpoA3v+TlHGL++IE+tq+NvEsf\niqbMwpL7uymkGuutBh1uMZKRPV0IpukUmmaqSppoijEZcJmSreNUTanBpCfqKo3shZ2uxmw2\nEFXFevbCrqESt033N1TirIVd87tNg6OYbg+DgPdPTsUacz6ePPqFXdbUF//a8f5Az6Qp4OAA\n4IInbhEsqyYghNQP7wQADMMAgG6e8jLmLBykQgjFPbfXop083r9lBTukgYGdBtnz/fxsr8/U\n6bVvvfTw6EdXNYKMB9DY6HTi1w689NJLx+0YNWqU89v2HKzxj5DGpXsgI0B8P6VMzQ+OlWiD\nWY1JAiHqOUjuHcRTaVHPwXLnVZ0NhMHwaaKH35f1GCAQittvq/HHhk0VPb5Y7qqqAwCBCEWn\nSBEC3zBh95PCzhCTJrb1NiaVrbaIShbZQncjkkQCd4Nu+gxE85fykkfwyhuwykasvB7rM5o3\n/2ue26oOALQB0siemsR+vuxLCGAYSkj1j+nty17VAUBUL21YvFdwNFspBgD+4crQeHVcqgfy\np4TES/0jJAFRkuA4tp52gVEilQ8fwyCu33WKmbCBADDksX8u+gU2Hpo/evgLu8j+b2zf9UGm\nW2kaOTi6grPY3XKoVCqAhtraWgAlgP7vjYeaAIAKuuPj1S80PfA7gFrdbohAXQxlZFVVPYAG\ngMj76Z3PD4TGjpgz3vjF0gO2GC73CA0NDQ0Nbfno5eXCI80j/to2QuIlIfGeyUOh8hEMuYfV\nSKkNxCY/IaYIOHec3LmW0usgMhEbM53XVX0tJ+kzWpEySuGRSkd9x8ti08UCEZKxThsbFCu8\n43kvq5FR+7G1lrz2IdL6wekc6JUKjzzP9jgxHgqJ9VgWMZZZju2Rq4Rup+Nuh0CIhSd4RkSI\nZbz0sZ6ZNhVKsJH3axnmelflQshBbT3XWnNh3dodz42e8mmuZOj72/98uc91VbMc/wo4YXfL\nkdC7twAKzxw40ACRXuA/58tnFvX/rCzjpaXPRawdcQlA2rt3jJNN5e7fb3hiihzEMzdSMwHA\nvGl22BcgTEnpcS0P4F8KTwA9+/N79vfkLenBkVLt67FZK4kcc772VDdIZfDsm1zo6y3CP1Fr\nlfFkSTHEOKXu6PKNj42c9m2+esxnOzc83fMGynLIcevATcXeckgnzL7HG/BtC57+1b5EAln4\n45Pv7KbAb2aPjQqEes4/3XaznQ+rEYp+Oc9+mW7Nnf0/1pVsefvegVFamUikufOHGlBOmDWx\n26cRXbH56RQZ4ofd8c3Z9gnqOTg8DHl9/bI4bDAMGBsphyXsnKGmxHL6QEPOjroL2U1OVm32\nCDaLnaf+OcnFj2+/+9tzViwwRpOz+PHZbfh4v5sVfDk42sJZ7G495FM+/fHR7DuWrpoat+ej\nEUMCinUAkP3awH1NuLT38z99mPzjSucaQgAo/6WgaAZposJ8vUW6Ej0DoM/elW2aMLh5pql4\n155qAOvB/84uLSQAmKyPBkQ+kFVk8Up+7td1jyT+O14ccAsFAEKxB2xaumqr1UyqfERiKdt7\nsyifLs6ntYEoPt3lIFZ7GAa2bWT2bgGxFCZPRynskm1VFVoL8kyklfENE8akyRyWyuiGYzvI\nnT8TjbWMly8aOV2QOoJ7ml0n6ivw7B2NhgYSABQafupotZefm36cpw82FJ8zNn8oNBeeNvS7\nTavyuR6JP5CLYbAOWnOuqca6OhIA6LKDP6882O67MYO+eD6TS1LMwR7uUXgLYdq7aObMFba/\ne4/KFJ27VJq/a22OlQAAymvII6899cKciTHSTT862R4CoEhMFROB1RRfKpSF9b9v7uDaz9/f\n8tVH6xYOvt9W4qA+/7weAAp2rSwAAICio4dtyxtoDxbYtlF8Fq8qJMOThD4hrK5bhoELxxsq\nC01SJT8xQyNTsYotOHO4rrzACABBUfLE/qy8jk4fqq0qMgIAxkO9Bvt4B7o/T7P7V/Kv5c22\nrORM3sxX3B8pv/2E+erD5hmr339mvliNBrqb+7eiwPr3xgbb3zWleEMV2X+ymzEBZw5Tv/2v\nue5KQzWz9jNcqkQJ6Vz6umuO1Uxn/dlgNTenfNPXk1l/Noy8T+tGxu+qInOrqgMAABKn8/bU\nZ97tfz1mZhF4cirWudXSFl1iFnlqnxwcncMJu1sIomDXTwVdfNf35dVLH+tYYTX5nUvNaeh2\ntl+eC9Ep7xaEPv7b2c9a/b6Y7aVfbll+9OgJuH+QbcUnH4ta9m7lrD91C6yPjJ25vCBo5vKt\n38+I7korrV69et++fS0fjx8/7uTBVV4hdv2oB4D8I5a756nFbiVms1FVZCrO1wMAbqHyjzak\njvJ1u6m6CotN1QFAWYHBL0zqHehm3GhTndWm6gCAppiCEzq3hR1FwvZVrTOUefup4VPpwEh3\nzhjDwKqlbQa/VUth4Aj3+gWXctuM4uWXLKYmypmcfx3J3t0+/1/2LpKNsLOaqZMHqrz8xNG9\nPRATcOJAldVEpgwLEAjZvt9UXDGUXmiMS9OyL6bXWGs9fbjaL1TG5hhriq0tqs6GxUjVlOKB\nUS5f+ZVXOim+Ymwkm+oIlZZtKLdDEADy4Msn5+3JccPACbtbCNVDO3TLRrZfmjU3uP9nZW42\niaWk92m9RvY+5jNmuQnA3NDQdjXq/LKJ/f/cakx9acum90f4dvOIO3To0DfffONGT5rqmscS\nEmeMjTQbYWc1tWoCs9FxfuBum2rjEmQxu98abmkzWFrN7jsbmfRMO8+zpnomMNKdpqwWMOrb\nLKmtcs5JvNPWTO0z+1tMtHvCzqBjoG1H9A2srC8GHW5oxAmcZi/sSILWVVtomjE14eyTz9VX\nmIxNhK7G4gFhV2fBLVRtuTm6t/uNWDr8iABgNbpQs6EFEu/8JyNxd1pzA09OxXqsJQ4Otvw7\nfKD+PRBlu7545o6BCYFqqVAo1QREJKQ/vbURAKzuDXoStbr9YIIAKOqq6DCd3nWkHsB6fNO2\nChqajn20ZH/3D7gFCxYU2DF+/HgnexKWKLQFZgbHCTUBrF5ItMGSFteugHDXaxTYofEXtTTF\nF2De/u6P4kpvIV/Qej+ymYdVeCH/8NamxDIUEuvmnS6WQHyvNkv6sMgV5x3QZkZYIERKbzd/\nyuBorN1YGhLD6mmm8Zck9vPpNdh9820LfAGWNNA3oa+WvaoDgOgUTXxfbVC0gn1TgZGK6N6a\nnv1ZZefptDadqwXrbMi9Ovn1EQK5+npYHBACDGM89Y9Tdhw3DpzF7laibs3wpGUHG0AaljFs\nwugABVFTfOVCzlEDADS0mpIwDAMgyba2JUKnMwJ0nKt1QPWm73Y2AABSRWsNl2pxeu/K3bV3\nDe+6Ha1Wq9W2fi2TOaurRFI0Za7aaqLFMrZvIzKloP+EgJpSs1TJ1waxyjcglvHTRvuVnNcD\nQEicQixz/4YSinm9h/heOtFgNVEaf3FMH1b5xma9Jlz3OV6UT/sEYZMfE8iU7g87Cz7DnptN\nl1wBAOjTH+a84n5TPQbLG6qIhioCAARClDZO5Xal0RHTBOeOUQ3VzS8sGn80fCqryTuEwC+U\nlcq3R+PvsTwWIgnfP8wzuc74Aiwklm2JA22QMChGXHaxNeI9NEHi5e/OyQ/vIS85b7SaafuL\nICxRLpJeF1/JfyyPHQfHtYUTdrcQeNb3BxukqS9t3f7eYE3LE+vvJ/wHflWlaH1Senl5AZSV\nlNCQ3LISlXs0x51ZRO3k5+5d8p/VDfeuvHjXGtHEVXjDpgnDntyw84sxfp5/0CEE7FWdDYmC\nH5rgARMIAOjr+cYmNQDoG5CSxSSeQcfk7sXKC9TGRkYbhBEEnTTQ5YpbLfgEo8c/9EyAXXQ8\nrD+AXcoHiRRCI1nlGxOKsWEzvOsrCMJKa/wFQon7v6ZMhR77QLxnLVlTQvuFYsPuEUg983ty\nOCZ9nJdfmKmqyAoA/hFit3N9i6S89DHaUwcamuoIAEAYhCXK4/t6LE109yDwpLDjlB3HjQMn\n7G4hyGoa0PCnXrdTdQCACfkAYCeIkvr2FcPGdc8PyJ9XeK6wnhD7RsT6mk5eadcabbQAWDbO\nlImtQp+4gXc9u+jtsA67lCekRVyVDzwEgKWlqrK/nDzE+uvubyYF3uIT/Y21zNrPifzjrc5w\nCem8O+cI1D4uP+MLz1KrF1lN+mb7U/F5Omc3mbOLnPGKWHA9Mj84oLaMMleTpBAaFQK1L6uf\nlSIZ3AKkFRE4CFlYtf7eTK3/irDanO+zqAObqDufEGSM46JirwcIQVgPaVgPD1TXUPkIB97u\nZzaQuJmWq/l81rEmzuPhdCcea4mDgy2csLuFQGIAU1lJKQPx3T1l5MOH9RRtPH7xyHFpcFyP\nJKyu4PyxMhIEPCBaHfHq/3pvZTkAQ4VOnTM5CFUcXv94/+MjUh059KOoefueXDvioe/uyrSu\n3r3irlBPDrQMA4SV8ki6ONxC11cSUgXPbR8vioRvXrdWFbfxXTx3jPr2Dfq5L8Q8V1o1Gxh7\nVdfCpTxqy/fWSY+5Y3irKsRzdxl01ZRMhfUYJIvs5a6zFwM7fzKdO9ycWITHNw+YIkke5qYt\nsKaY3Pdrk1FHAwDGg6RMafIId8RB7j7q50/ahIdYTPDTYkKqhF4DOW13PaBIprbMghDSBokw\nHitVU1NCnj5gthgYvwh+ryEStysIuwxiEPJYuhMADzbFwcEKTtjdQgijgqlTuW+PHVf3zAMT\nh2X0SQxTd2LtIQ6889FxK6gjYuUNRZfOGQN7jnrxlZTsea9t04OuzrYOvvfNh39rAADJ5Pe+\nXzwBAGDBk68P6veuDsCBAYkXO3vNftGs4fevmpZpXbn7pxmRnklboKvB8/bUWs2UwkvQZ6SP\nmIUXjq6aOLShnrDSABDdR9ZzkDteR7n7qHaqzkZVMZO7j0ob4UL3sneRHVVd81c7yVEzhRK5\na0NdUx21b00jSTAAoK+nsv5oEopRcKw7auzsYbxF1QEARcKBdabAKL6v65KdxJm9vzSZmpoD\nHmkKTuwxeQXwwxJdtkluXtG538Cm5SQbYcfQDPKQDYdhgGEYzEOtUSTN43vGlEUSFF/AVvsS\nVvrQxmpjIwkAci/BwMk+blvaasvILd80USQDAJVXiJpicuxDyutj/kIAHsy1+U+UROPg6BxO\n2N0SiGduYmYC4BfWzHv4+aXb/vvctv8CgEAd3itj6Nh7finDBwVelVf09u9XloJk/KdZm2a3\nBgAy52p/6fH6KZUXDQBAbV/xYwWoZ2woWTXlqte2NOXVd2YuHb+8NuD5Y4WL01q2bMmEt2nd\n1UW8iOmrrkxf1WlPly1btn379paPWVlZTh5i/tEGWwYQfQNx+WRTYob7sQX5Rww2VQcAl3KM\n0Skysczloa7wbJcZGa6coV0SdmUXu2yKoqD8Mh3Vy7XuFZ+zkEQbpXjlhMU9YVd4pkPFLgZd\nyiXcEHZ15WSLqmuh5JzVVWFnbGI6ldQAUHGFMRsYV3Vwc7N6S35uqUwpjk8OdmNze2iaOXG4\niCSopL6hYinbF5sr+VU1FY3hsb6+QW4mc26htrKp4GyVTCHumR7Cpp3ifKNN1QGAoYEouWCK\n6OlmeMfF41abqrNRfolorKVUPtcpeMKTeew4OG4YOGF3KyGMHRiBl1lh4FNfjBPl5mVn7ft7\n64rsrSs+XzJv/Y4PR3oBABTk5DQCpA0b1iatA0oYPiwATl3JzdVBH/Xl3NwmgGGZmW0e1tLM\nzFRYvo1dF3Nzc9euXevGhri1VRPYSni5DdE2YxxuYcSuR0MSXSeQ6earztcnulufxLv5snNw\nU/sG22WUdR6LsUPfkMsHeLUPnWxl7dBVh+DdFtTErSBxS2OYjThF0Sa9labZWtpInLKaCVub\n7IWdUW8BAKPeA3VETQYcAMxGK8MwiIWJibC2uZza3VAuYemQAK/T6+RagAAwz03FchY7jhsH\n7oXlZkC3bCRyiPzhrVfX1/Z99LWPlq3dfbqq+tRP/+kh1Gd/dN8be22ml8bGRgDw9/dvt4+A\ngAAA0Okar67D9/NrF+Mp9/dvL4BMp9d/8sZT900Y2CPw7h+sANRhBxa4jz76qN6OKVOmOHkO\nAiOldn+zSksRYJciX6HhKzpLpuUQbVCX945PsGu3FYa6C0gWCF1WsdqQ9mLCJ9SdEAyGAQo6\nsZ0wbhk6vDvLPqgNdvnk83nQlQsjX8C45N1oj7evIiLeP653EPv5U6GYH9c7MDLB10vrgfwp\nkYn+IVE+wZEu5yLqSECoV0iUd3xyEBtVBwB+oW3CXnzD3E/XFxDVeq0yACIp0vhfLy9JBBjm\nsX8cHDcOnMXuZkAYO2bWLLv5obrj6zadMfr2u2ecXZ4B8cAgAN97vjmQ1uQd1/y7ImXPe7/+\nZO+GMd9W7thxGoamAKhUKgCorKwEaBPkWlFRAVe/ValUAEVVVfUA9trOUFnZPtdd9ab3nn8n\nG/jK4ARvcUVZJwWC2iGVSqXSVokmFDorOKKTVQovoUFHeAeI1L6sEnlEpch4AlRVaJUqebGp\nMvemY/oM4+36hSA7TFTyBdBnmAsj04k9DRiDA3RuZZIqqfysRqW3tzbIhUOWKoWYQEgTzbY+\nBvFlGpeHXosJPn2Fyj3A75eKC4Wtho3GJt5nC3ml5fSMpzCXTp1EgQXGCMsvtlogBWIU3tO1\nn7K+il79nlkoRGayk32LBMzKt0wzXpOofVz+URGGfALY5nhrwcvHYynxpDKRVOaZzDUCIS8w\nzAMF07z8heljtUVnDQhBWA+52sf9yO24vuK6MurCMQvDgEyJZd4j5wuvk+0LedTMxhnsOG4c\nOGF3MyDNnLci0+7z8Rf2bjpjjJn52Yo57Q1vgb0GBbZdggkEGLRWi4hKSVHByTN799Y8P6s1\nAT1zfs++CoCIPn3UABCZkqKEk7n79xsemdIqOEz792e375l28uLtI4NTkqK0ovnRaGFXlWo9\ng1+YxC/MA3lfEYKIJGlEEqtkDd7+6M45wnX/wyk7cxuPB3fOEXr7O/uQv3zCUHzOJFOBX6i1\nqrj94M3jMZEJZopksrfVD5nq66Qj4JFt1PovcJIQSeUCqYyyWpFex885gA+5gz/xPwInRzKK\ngg+epXIPMQDoWI4kIhxXKymaRrX1/MJiAcPAum9pAJj5jLP6yWJkdqxoqioiEYYwDBAAwzAm\nPWz8vHH4DHlIvFPKALcwaz4y62pohQyRBCKINgcjFDAyOd1QzaxZbH5wofT6BVf+K/ENFfuG\neqCuBkIw8A5Zn9FSfT2pDRJg1zOm2bM+dtzlxnHDwFmQbx2yljyzeNm8VITQlFVXxQbTePyN\n51ZUA/DrVoxXSYQSdfC8PD8FmDe9/eqOuqtmmOyn/OJfO8Gg3lOC193RN0yjuHstyQfdL68s\nOG4EumL3h7OHxPnKlBOX1wIAbu/zJU8YOiotWvvvHEOV6sZ+o+pDYiwqb1LlTYbEWDLG1Cu9\nGp3cHLfQF44112ENizWHx5uE4mZ/I4RAqSF79DXIlKRtzfNHm5xp8/Tf1K/17pUOAAAgAElE\nQVSf4jY7osmA1VYJ9Lrml7d968ntP3UwMHbBXz/TuYeaLw+LFTt3Xnz4mOxItrTgipCimn/s\ndd/S50845aLE0LBjZVNVEWn7myKBJIGiEDBAWJldPxrqypzKjp21Ga8rpwEAYYyXhlQpKbGY\n4fMZkYhRqSi1hrRlr6gpoY9scfZIOdyDppmmOrypnmBoVm5q+nry0PqGrd9WHVhb99fS6vNH\njTR1/fKGcCXFOG5JOIvdrUPtse/mrTQiAPj7s9kPH5ASuopLx/ccvmxkgO+dNOS2ATF+Ukv1\nxcObNukBwwqW3dYj7467RkRJG0799kMNAFInKX+ctyp6/Kh704j8rWt2XcHzFw+M2xrcdK5K\nEqSw4phager1ZNW23TpIuxqfV7z+lTf/qAAAyKsGAKjbOnt2LQCAdtz8xVPD/5ET4QSXT5LF\n50i5F9YrUyAUu/NILr9sKLmgV2qgR982kqvkvF6pEQZEOnbgL71gIvBWJecXgvuF4ASOEVYk\nltEYxrRd2dxjoLr7WSqSgA1fdSdodv1Cpo/iaxwVBaFpWL/MKXf4tUvp1790bGO5mGOtKuxS\nupEEc/hP04THHEyD0hQc29Z6dAhALKHFks77eWwrPnCykPNnv0bUV1hPHqizGCgAkCr4vYZo\n3POOaKoj96yuI/HmS91qpk8f0DdUEhmT2Mb/OgNCXIJijlsTTtjdOox4b+/vCW/85+Wt1ebC\n7b+erLfwFT7BPcfNHDzuiVef7O/V8uAxZb85ZNDbJ4PTw5r2rvx0AyH2CfZTQJFed4Fe8Pfp\nN1OVAACGGQ/Hjf2ugq48UwgCudIr9d4F778dvNB31DrzhRVLL774UoytsfqcDStXnm/thPHM\nypVnAADCtHM8KuwokrmYW6vXWbWBsogerOqoHt1i3b+uOcbw9AF8xhsygetuPSX5+q6+Kj6v\nd0bY1RR3EucoENKdlpqgKaa2zOof0d3k18U8SlfTnbWDIiF3DzVimoO7/uIppqG2+1WaOZHF\nWC0gcjQjdzHbQURn5WVCX08rNN1NIJQVUGaDs7YcYxNTcZkKjHJtYo99PGwLZgNBkrRC7Rnf\nOGA8JhxoimGZT5iw0nl7avGrkbAmPZm7u27wnf58gcvzP2cPGVpUXQtlFy21Zbg26HpUXPkn\npL/p9Pqv1+zJzc3JyTlxvsJI8aauJX+56/r3g+MWhhN2tw6SwLRJM8a89/LW6hGflm+c2f6n\nZUhTU6PBQtBM0F23p7x9PC/2NX3WJB4AQN7r0Snv6sMeXfxa6lWziXzMA/cEfPffCuXMTWU/\njr/q2Lb21KKU6JfP5p2kIcb2FE9+J9+Wxg42zRZPXEk6ekh9/vnnf/75Z8vHU6dOOXl0ZQWN\nVcUGAChu0qm0Yo2f+852x7e3zibXltNFZ6joFNduBIYBg67LNCSGBpxhHI8ZJr1r1XlNTQ7W\nr7jsWPeUFTg2xZUXOdslAoeaciY40sGh1lc4PtL6ClKh6W4s11W7llOjoZoJjHJhfaMeP3Gg\nXKkR98xo77jqKk31lhMHygEgJtnHP4xtCduSC7qSS7r4VF+NH9sSXg3V5jNHK30CZXF9fB2v\n3VUjVVa8bX4Tq4nSVePaIJdd7mpLO7+Jakuuh7BDAO3s4qxac1Yj2gWcBWmrLlR5qgMcHC1w\nwu7WR5e7fOH8L9ftyStpqyTKyuoBWuMnoOiz/nemES2KsPFUPQAIJGn2CiooKAggr7S0BsDP\nrc6cP39+586dbmxI4rTd3yzy2DFAtLUf4RaXH+4MzTBdb8QwwNAMcmQXYVxM/kU7Wp90QihS\nTqxDdptXrx2EE2n2aE90zJme28FQrhwFAOBmkiJpk971tIEdm7qaZ9Fqdq3TnWLU4xRJm40e\n8Bq0mAiGZkwGVk11enm4erZtdOVOR7HKU+k0/0yCYruAs82zxRNXeuAS4eBoCyfsbhkY/YW/\nli3+8RwA/PWQVPCwSKkNievdN4F3cPWfBZLe0x9/f1jvCD+VVMhD1p3zp3x8xGptI3AwgDbK\ngYchABDKVPYL+Xw+ABDE1ZHBbloh55wVAA5nAXRnsVuyZMmSJUtaPk6dOvXXX3915vACIhXV\nJUarmVRqRN4BLHJJIIjpwz97uPkIRBIUmuDyXYDxkFjGtxg7fyaLZXxnZrtEUszobKAFAIBE\n5mAU0gY43qm3E+tonY7qRciplRXeWH2Fg7Fa6e3g6BQal6bNUPcTux3x8pUmDQiQyDxQAc87\nQBbVS0viVFCUyvHajojprQ0IVyo1HpjV9Q9ViCR8uYpVU2rf9rY0jIdUbmU8UfoI6so6UdJq\nn+s0MHlyKtbZpuQJQ0d5bq8cHJ3ACbtbAqZmz8Lp0xfuqqIxHgD4pE0fF0c1VReePLr6+xoC\nsPCn167+IKZl9fPZr3RsQzTug+3vj3HxgnA5j53bSGSCfmODcSslEvNZ+huNnCmWyFHRWVKh\nwQZMFsnV7jQXECG7crpzXRYQ4ZTu9A4U1Ve4YB/SBDoYj+PSMKHIQWGGXoMcu50l9EEO27ER\nlYgUTri5h/cU1VeYullB4YVpgxxceiGxPJ4AKOeMTXwhBMe4bI1Raz2QTAcAEILACI+lxOPx\nMZW3BxKLAADCEPv5XKmCH5euPn9M17IkLl3tRlE+iwkuXxCpZO1vAZOJV1osCIpl2U3HIMR4\ncioWrl8wLwdH93DpTm4BLNkLx4+fv6vWf8w7P77aBwDSH/9u2ferft10MP/Ewj4AoJRK7e0l\nFbt353dsBfNNHJTg03F5t2gnL95+7GKNQVdy8qFAx6uzA2FIJGGr6gBAKEbDpolnL5TfOVca\nEOFm4qzwHiplZz5hSm9heA+n7DRBsS4Msd6BIoncQVdlSjTs7u4MTj3788ITHd/yYgmMvMOp\nJ8OEmU6t1nOQWKLobs20cVKHP6tQjBL6OmtOS8wQcHnsrhEMzQACmZcAYYDxkEItAIZx1a8A\nt8KiOcSeTYLcozIcb702aqv5h/YovniV2veH+2XKnAchj/3j4Lhx4Cx2Nz+XlzzxzjGzuO+i\n7X++pFryZ5vv/BN7yCBH0Dvhahhp3mvhKe8VAwBA8Q+3R7+XX1yrenrlbAAwr5yIdD8SHaMu\nWqArNs99eRMAXMi6aIFgMfybpxV4fJQ60u98Tn3lFZPNVQjjoYAIWWyqhsd36jGv8OKHJkiL\nz3Vnymohob9TFqCR9/KrS+jcfZ3MewbHYNOed1YYTXsCO7aPrinvbp3e/dGQ8U4dqVCCRs1S\nbF3W1Kk7Y++hkqhkpyYHh9wtvJBNOvSJFEnQkLuuR0zlvxCKYnJ21NRXNptzGYYxNBH5x3Q1\nZZY+I7XOxxSv+YIqOM0AQNEVUXmZwEtDi8RUUyOvsaH58bPiQzK2tyAg7BoqJr4AEjNan3ZW\nE1w55YLDW2QvvtDOwsv3wBw+B4dn4ITdTc+J5cuOkqC9f/7cHgIobfclGj3n6cTV7/98f3rF\n5rsGhAlr939fAoD5elPVdRVl/PFjp2Yam4KdGQQt+d/OHPv4b5VygMbYjJirU0M3aR47ACCs\nNF/gWlGsduBWSt+oFyloWyAFQtDU2IRblBK5s8/4HoPUumqiqc7B/GJif5WXn1NKBcMgMZ0p\nOk00NfJJsnlQ5PFAriDjU3gSubPDpNILXv2c9/IM0mrtfBNvLTNvMd/5s+cbyg9JoMvOM1ZT\n6+wXT8AoNFSc03Y4L19sypPi3z4zdxNIwePD7XPEKi03F3FNuHyiqUXV2VNXbik8rY/s5dTr\nh66W2b2+9d2DwLHqSqzdYETi8Pty6rH513KEamtpQ4hBLs3MIoZlyV0OjmsEJ+xuduoOHcoH\n4A8ZNaxTo4e478IdO71ffvO7XRu/ygKvyPhAL6ipq64HgJSX1m58LhgAIO/1L7rfSf3BtyZP\nXniIN/K910WvvrHZ/pvrlceOpuH4FmNNCRHZW5TQn5UvFE0xx7bW1ZZahWIsdbRGE+CmL3nR\n+TqSoMHOBZsk6KLzdfGpzubL4AtQz8Gqw3/UdjOTJVXzolIcZ8VrhoHcXVa5gpYrcJJEFIkw\nHsMXMAjg4jFqyF1iqdJZxYMb6fBAsrqep2vC7EOAeRjj7UVrVRQwfOc9xusrcH09rvQBhkYk\njmgGeHyGL2AAoOCEMWWEswlpY1P5Uanic39beJ3NS1MUJAwQu5q8pgWrmRIIMZZp3mwQOEWR\ntFjqATMOTTHGJlyhFrF3Qii/bCgv0MuUQuftyvYwDJReMHT1bcl5g5PCLu8Q07HIckdy99M0\nDdg1k+gUAeePtemHSzqt8HSb14teQziTHceNAifsbkbSFhcyi5v/rqqsBADv4GAxAEDw3Cxm\nLgDAieVPfnWk5aVYOvS9I/unBIMtZd2JOu19fxWtHNfi4pX8zqUSbUbIs0fsd+LXNwh2VI4Y\nwS/67cGxM5cXBM38cev3M6IFr7xuv5areewWLVq0bt26lo+XL1928pivnLCe/dsMADUlpH+k\nwMvP/Uu3vMBcW2oFANxC5x9pGjDFVc/CZhrrOgkW6XRhN+BmiidgaBoYErVJoYIAQ4DxGYp0\nIfeDSc8YGppFIp/P8PmtLTI0VBdT4T2dHSeri2kexgRoST8NMpoRQQJCIBSAVEzbxr/qUlqu\ndtZDUVfdPIIijBGImbZfuZZhpEkHlZUCmYyWSmiBEBBiGAbhOJjNmNHIC9W5KX90NeYTBytl\nSmHa8CCWEook6Ow9xRRJ9+gXyD4gI2dPubEJD4xQxKRo2bRjNVH5x+oAoKkelyr5YQkuR+zi\nZqpdBjt7LEaKsNICkeMLrLLYKcOYyQC6Wkbje62sYgh5UjVytjuOGwdO2N3s2BKqdZgTuLJr\n6dKfWhVBlPqxhVOCWz4mDxjQveN+3uvRKe9eARCeXzax/59bjakvbdn0/ggPPGJLSkqys7Pd\n2JCwy1BPOhGw2Q002doURbofy9ZpKrtu8tt13hkGAADDAIQMMMAwAAwAZmc8cMWJnO6mcCdy\nnAmvbVPNf2AYo5B10iztSrKxbvL+uXzGKGAYZDDwDAYeACDUpgXK3UqjNuMrSVAMw3aKjaZo\nimxujU079h0jCLbBBBTV2oJ7l73DX6q77I5teuLsHl26xtzAtblXB215rCUODpZwnig3CZZV\nE1Ab+CKFb2SfcQ/9XKMGgNqSEkub9aesIhmGYRim4n8DOzQmDQx08m2dvHDg7wpaHDlkQp9O\nVZ3p9PpP3njqvgkDewTe/YMVgDqc1X2DS5YsYey45557nOsIRKWIgmKFQgmK7yf2CWH1QhIQ\nJZGr+QCAYSg6xf3CAJ3mA5O7WEVKqrA7FgQIA8RrMyUkVbpwsDIlJpZ1OcJog1wIAfYOcJQ2\nL9CFp4dC0+VEldLbtTksv9A2B9hOS/iHuvlM0wbIeg8OSBkSiFhXFROK+b0GBiX2DdAGOD2H\n3jXJmQHxaT6x7Mx1ACBVCMISVHwBptKKgmPcuexFEqybumFCMSYQOXWB+TgXQC8Qglp7DeWS\nB0NiEeJ0HccNBGexu6kQxk94YEgQAABt0VVePLpn6/fvgkgKYNq/Yw8+bZyToYDOGyREE5fs\njPt6zKuLx46g/tj+yfD2g8v1y2MnEKJRszyTG0wgwgbf5dtUS0gUPJHUzXQnABAapzmTVW5v\nJMMwFBarcakRta9QLOVZTF2aJvzCXZjLQxgkDRYd29pW5QMDgMJ6CBwmAbYnJgWTyFFX5VlD\n4zG1jwtjmTZYKPfiGxqIjpaN8J6uZVZLH8Hb8kPnp4svgPQR7r6sIlBrPZMuDgAUao81JZbx\nxTIPCEQAiOqljurlrDtjRxCGAiKlJec7d7MLiJI5+VxJHoD9CI5tcUkZ2LUONfWkA5/Td0Nr\nwFnpQQKAObJk9uxNADdBwBnHzQIn7G4qJAOf+frrkS0f6ap1M/vc/XO5AIOa1fP/+/zIFxM9\n/iCUp7+yZbdkyqhnP50wzLph5xdj/OwfYHblceZHo4UFnt77tQLjIbVzcabdoPQSJ/UPKsyv\n0zdYAEDhJQ6P93bVYocQxPdT5e2p7/RbiZwfkeTaoN5vgrimlCo8be8VjjQBvNGzXHP2EknQ\nhIcFa//biQOcUAyTHnHt7GEYSh+rObK5ztTUOqJjPJSQodAGuXbGAiPQhAd4m5Z3ogzGz+a3\ns+dxeJaYPqr6CouxQ9lihZcgurez712+wShjNJa13cHk8sTZ7r90OQViEPJgVmFnm2ofcFa4\nd2UhAHg+4IzjXwsn7G5mML8pUwZiP6+lE6IkZ46+Omoi+f3Xz44R53z7zY+btx04UVBaWW/l\niwAADHWW9hvT1Vnff/TJD5sOniyss4pUMgIAysrwdteEMfvte99fsT2vUSCgT385Pq1u3ZHV\nU1rn4P69eexsyNWinhmBXfg5OktApJTEmbNZunalMxVegpSR3t1MfnUKjw+TnpRdOI4XnSF1\n1bTcCwXF8HsMEPKFLncvZRgf48GmZYSxsbVjviHYnU8LA6NctnUoNPzh9/oWnTHVV+Ikzig0\n/NBEqW1O3FUmPMDX+KE/v6caqps7pvFHkx7kZYy9xlLgX49AhPUb73chW1dx2WRz1OMJUFCU\nLKaPii904ZK4/wV+wWmiprxLMTT5QV50z2ur0ZFHS4o531JrwBkHx7WBE3Y3NfVb/8qigZcx\n+5d3DS9Nf3vba2OjP4yIEF8pNPj4a6VilVJYXm2gAKBq1dMfPnXoxV5XDXrU2a8njnjyr0pB\nUMakaXOi1cSVHSt+qYPCs00ALRNjDIBl8ztfJowdec+D4uqsjRuO15auubMvWvP3qrtCm0fQ\nmzePnQfRVTMA4OXn/igREi/zCREf3mXMP4UDzYikvCGjxZE9JO75eyEEcenCuHQPJOntnclP\nzOAXnKBqy2iMhwKjsLAEzO3hEOOhiF6yiF4sSv1eZcBtvP5jeeVXmKoS2j8MCwi/sXKKmfQM\niTMuzX3fLAhEWI8BmsT+GrOBRAAShTuDiEINr3/D//wlsuBMe23HF8Ad/+FNmHU9NPo/MhXL\nwXGt4YTdTYU566u5czcBANDWxupLR7fvucD0nL7k2yfTekp2Xpy++buvf9q05++TCgHeUF1H\n+QTHDb3voQnTpyYefHjM2/NfXfOfTTNt7TSsnTrnr0r1mCUHNzyRIAEAKPXP+iXnSJ++9kEV\nDAATs+jc8efVCADot1fdGXvfRkP5L9MyqZW7f5oRKYDrmMcOACwmsrHW4h0gddWI1RFDA1F8\n3ihT8sMS2Xov7fjBfGo/DgBJmcJR97uf26K4jDdhutJ0tQ7FbbfB5s3dbuCImhK88LTZN0wY\nlsgq44ZACD6BdPkFg1CEfEMULPUTbqZzdzea9XRChtwvnFU1en0DvXe1vqmOVmqxSU8oFBpW\nVwVJ0NUlRolc4OXL1j0ue5vl8B8WAIjrKxx1v+Nqad1DkbSxyarwErOXrjTNNNaaZUqhUMz2\nyc/QTEOlBRAEyGTOF5ywR+OL3vpOcGQnffAvquAUjeOMyhulDuGPuAvzD7keKsmzpcA4Xcdx\n48AJu5sK/Mz6z87YL1An3TV50sBICQAgZdyEZz+d8GzLdwxpamo0WAiaAf/bU94+vnv7AWrm\npHcuMW/vetxvJCXMnP91s6oDuwR49oQ+fTDbpuoAAPOf8fhdczYuFz+5t/CLQVdXcTWP3Vtv\nvbVq1aqWj1VVVU4eOsNAzu5y3Epp/CS9BjmbAbgrcnbW2fyE5GqBd6D78qKhirapOgA4tR9P\nHytS+7opLzZsAJNddbEtW6C+HjSuRWK0QtPw98YGEmeKz5q9/ARKb1Z3+tG/mhprSAAQiLF+\nE1iFsJw/Zii7YAGAY1t0Ex73Y9PUyX2WpjoaAJpq6VP7rQOmsNKvBSfqKwoNAJA6IkDh5f4l\nQRLMkU3Njg/nj+LJw0U+IayMT/nZlY115qAodVicN5t2AKDwXF1FYaNAyEsfGcZSJhad0xec\n0AEARTChCW6GliMMMkZjEoEhKsxoWzL6AR+Z+vppJE+mO+HguGG4BWcKbmVUD+24migE11cW\nHP75Ec3+d6f3H/5+jr0zsy53+XOT00NVEpla6+cfEBAQ0Pu1wwDmsjKbh/7lrKwagIRx48K7\n3xuWkt7HXg+g0NBggIaGBhZHYDKZGuwgCCcy0F/F9gx2Ne1ZN015vCFXS6G32ZZp/5HVkTJM\na99YH21LT5xMVOZUm6x/Svuzzb5j1+qS8NDJ98yJb26K8cTRMlf/89zl5anDdBKPpjvhTHYc\nNw6csLtZEcj9IjOmfbB+8W1iw5GFr6+ua15O5Lw9bOCDnx4gBj3+/jc/rft90+bfvnlrVooG\nAA48FyIUyryCRn55AQDkCkdmL4n6aoTnpUXJCPGn7eTzAai26UWZprMb3p81IiV29s9WAGrT\nc4PufnnF4cquinl+9NFH9XZMmTLFyeNFCPoMC4xP1Sb2dbNQhD3JwzSB0dKEfmo25joA8PLH\nEgc0u7IlDhB6+bt/Q02eDBI7k9OYMeDNwkCD8VD/yV4h8eLU0Sqllq1hvu9tSm2QIDBa1GsI\n25nr2DR5YJRY7StIG6NiORHWe6hY7oUBgEKDJWWynT+N7qWJTtb0GuTHxlwHAHwhSh/X3JmY\nVIEvO3MdAMSn+vfoG+hqGp1OCU/0jk/1Tx4cwj5XX1iCMi7NKy7dKyTW/UyQNmLT5ZoAgVCM\nxWfI5V7XbxIJASDMY/84OG4cuKnYmxxNenoU/HXm6NFTcP9QACA2f/JRnjno0T8OfT1SBlC3\nb+HUexbsqqYRAMjjx9+eItNXndm1rRDg0PPDPhtz7JloVrtv3D6n74QvL5Cq+NF9wi/vuUAr\n0dn1Hzzw2/cblh/9fVY4++OzRyLjS2RsRxEbKq2w9xAPjJQAMPZBSfpYIQB4B7IawhMSYMsW\nePddKCuDoUPh7bfZdsw3TOgb5oH4CQDQBgtGzvLM6RJJsYxJXh5pSqnFZryu0jfQCi8MY+1q\nzxdiwdGeSZSYfps4YYCQxMHteXl7+AJMxboumQ0MQ97+HohcAQCMh0LiPHMzShS8IdPYpl92\nBwQeTHdyQ8XucPzL4V40bnZqamrsP9YVFuoBemZkyADwvPcm3PbWrlrfIROThQCQOOuz777/\n4dfNx399SAvAE9fk61ju/PI3r3x5gdBO+ens2a3P9ecDYJkf56+/L5Cp+eONz4+ybPzmwTuQ\nx1LV2RgyBLZvhzNnYMkS973r/lVgPFBpPaDqPI5cjXlE1XFcUzDMY/84OG4cuOvxpsZy4cv3\nf6oGkA0dmmZb4hcZKQPI2bmjHgq/emJ+lknY5/m53kfz7KuromFznu7JoxqbLh3Kb0lvR1dn\nLX1yYv/4QLVEJFGPXFIKgBeW4ACXFqWhmFdOAFBrnnrjBAC15naEpqyyAABcuXwZAPpOmhLY\n+rrqO3HKQD5AbVvByeEEFjPs+YtZ/wNzNu+f7srNQE05s/4r8ps3iA1fk3WVnBc8h2sgj1YV\n4+C4ceCmYm8qzIc+e+yxdQAAQBqqi88c3ptXSSCf2/676M5m3yc0es7Tiavf/2l68oU40zEC\nxCG137xWM/buAWvW/t3SDJb08pr/HR4+Z8vc5Og1kyYOilFWHfhpzYEyK6ZOu3PanGg1cW7T\ntxt11vwTTQD+E9/+UbDytRfWlGbcf0f5D+tKM+aufHLKQCEAQHyPaAyO714wbuq+8Lrm8jjT\nR5dsJkEYrnauIOQ/BkkwPL4Hkp/VlROX8ywAEJks9g50v/JHcQE8fS9dVWb7xNx2N3r9E/e7\nxzBw5aSltpRQevNiUiU8gfvHaTUxhzYai88SPB7E9xOljZWy8SgqOouf2mu2WpiQeGGfURK+\nux27mEf/bx5BXK2LsWc99czHgqgk7k31+mFqIgEhqYKtvVRfT509ZDIZqIBIYVw6q6vLNTxa\neYLTdhw3Dpywu6nA8zctzbf9ifhipW943zunzXjmxUcGB7Q8VcR9F+7Y6f3ym9/8cbgEAITK\noa+vWPR4+eNr1to3JEh8/M+8Xt9+sHjFn3tXfbbBSpEEJQi67aM/NzyTIgSAPP6mjWcqMgep\nAAQ9xs0UnVj8wpqysPTe5h/WlYUNmTlziK2ZoIefznzx/r1F+35duc+2pHDvL4UAAGAVOS4G\n6QoMA/lHdQ1V1qAYWVgCKxd+hoHcnfUVl81iKS/9Nm9Xi9Db01BJ7v5RZ0vBX3jKMnKWl5e/\nm/fU+y+2qDoAgL/WMumDYewdbg4XJ/cYzv7dnD2l4jI+7F73K4QeWGe8cgoHAAIgb49FKMV6\nD3UzUqGqiNyxQm/7u6HSjJuZQXe66fK1ajFJ2FU7I6zwwyJy/iqh2+MrTTP11UaJVCBTsgqe\nsNFYb6YI2svX2fKp3UASlKHRqtRI3EsXZw9uoapL9QovscqbbazJ6QO6K6eMABCVLE8coHK4\nfldYzfSOFQ1mAw0A5Rdxs55OGemZwrjOwAU9cNyScNf1TYJ45iamDTRh1pWdO7ju08cHB7R9\nZeYHDn3+h/0bno4BAL8Hvl75wvAA2cyNDMMcnBtstxrPf+Bjn27IulTd9NfDagqEmR8f3GxT\ndQCQ/M4lhjH+OrOt5PF/PY9hyF/sAlnF9+1pyF/9qH2VSGnclNdXn9AXL07r7DjmzZunsWPj\nxo1OnoDaUnPRWX1THX4uq8FiZCUa68utFZfNAGAxUZdy9WyaKjpjsak6AKBIpuhMh8ptzoFb\n4VR2+4XZh9zv2OWTrT2pvIyb9W4mYqFpKD7XJiVN4elOqsc6SeEpe5cAuHzS6l6uDIOOqS5p\nv2V1KaOrcd8AU36l4UJe5cmsUtzaVUi3s+h1ljNHyvNzKqtLm1g2BQDnT1SeyykvudR5NWGX\nuJhXXXiu/tTf5VYLq2O0miibqgOAgjwDYXU/zU/VFcKm6mxcOenmHeQGHpyH5dKdcNxQcMLu\nVsX5+qXOprXrjIb9C8YOmrFe9dhPR67UGI31Rdm/zQs79u69/Qe+eia1Z0MAACAASURBVNDc\n2QZSqdTLDoHAWWsZxms+EoQhlq7KiNd6UlhaQdr1xO2OIQw6doTPwp7eriduWyZQh23ZnPx2\nZxvD3BwOMV7nFzarvvEwAEAIsZ+e5/Ga+8Hje+ABa2uNx/eAcLAdI8ZD7leFAwAA+2wpCAGb\n5Cntry7eddVHCGM89s9zmRA5OFjCCbubgZ2PqRFCY5cZOn5V+/VQhJD/nIPtvwgIDASA2uLi\nTvWVPTqdDgCCgoLsF5pOr//kjafumzCwR6Ccj2JeOdnZlsbtL02dvxemLVk6uvbHuRN6RYTH\n9b/vizM8X4np5AfPLC3qZJMFCxYU2DF+/HhH3WvGO1Acl6b2CZH0HqIRSli59Wj8hRFJch4f\nqXwEsWmsUjZE9JbwhQgAGAC+EEX0djMthUAAaYPaD2n9h7vfsbi+LSV/IayHWCxz805HGEQl\nt8mZEt3H/ZnKqBShvVNdbLqbE4JSBQRHtz9dobFIpXVfFgSGq5P6BfcZHCoQsnUakyqEKZmh\nSf2DtAEemFWM6+3fq39IcKQHwqRjU3xiU3yTM4MFIlbHKBRj8RlKhAGGocQBKrcdJQHAP1Ko\n0LR2JibNM4ldnIQLnuC4JeF87G5VNIMGJcLus/u27bJOn9DtUKxWqwGgrKwMoDWpXfWm955/\nJxv4yuCEIG3VhapO30ZzNm+uBEhrWNR3ZI5e5NMzI3OCn9BYU5J3qBjoU9l5NIR58s0hIkkR\nkeSZ1FmJA1RsHINaUGh4Y/+jKTxpAQThSWK52v3x8pWP0LwHmPOnAAAEArj3MZQ5xv3hIj5D\nqvbj15QQSm9eaCIrh6oBU6QiKSo6TfCFENdXlJDhvrDTBPBve1R5+oDZamZC44UJA9zv2P0v\nCz6dS5j0zRemTIlmveq+r6QNhRdbz7MWJDIBANv+2EAYkik84PYHADw+5hvsGQ+2mD6KyCQ5\nILamRIEQjXnQ6/wxs1lPB0QKQxM9c6ROgTzqY8dpO44bBk7Y3bIkPfBI//fnHv5l/sfPj341\nqZNEtbTBYJXLJRCZkeELeee2bil6+amwq19qJy/ePjI4JSlKK9o8WzxxJQ7AUBTT9vGF4zgA\n5G7Nkfd/efvaBaOCbHup/d8Qn6f3C0WiW98ebNbTZw/hteUMAJj0eFKmWCJ38wHv4w8vfYL9\n9jNUljGpGWjaTLZ9848Q+kd4IEExX4DSx0rj+1I8PrBRrjZ8Q/mZd8sJnJHI3b88CCtzcp9V\noyaFPIwkQSAAuYI+uY/2DRLzPZOSmcMxbEKt7RFJsV5DPJM22SUQeDJBMQfHjQMn7G49zAVb\nliz6ZNWeM4UlNIaI7NfSQjbO+mz9N9OCASDv9eiUdyvv/2lb4s/TPjhGQJPOKguLD/bHqvfN\nf/SrURsfj7cZLeQJQ4dWlzbYO8/QxcWlACF2e0rrH8//+iCJ/Kd/uXBUkM0+QVX9+fLHBwCk\nI0f2v37H/I9QeJrYtcqIW5rHhqIzxKn91hEzZeE9XTbV0DTMmwdffAE4DgAIvocF78Ly5TBs\nmJt9owim6KzJ0ECK5bzQBIlY5qYgYxg4d9h8cq+RsDIAIFfz0sbJQuLdNKs0VBI5O/S1pQQA\niKVY4iBZTKrU4VYd+gS/fWa5fJJEAAoF1bIwZyfRVMfc85yEs51cByiSaagiEAIvPwEbxzia\ngjOHzFdO4hYjrfHnJ4+QaIOv16iEPJlY2KXZWEvB7x+8+fHqXXlFOkYZkjRs6jMLX50a5/qt\nwMHRKZywu9Uo+2Fq+qw/jf5pEyc/PNWXurR1ze/HKo59O6PH3v9l9on2teZWAZhX3zeIpDF1\nvwfmjPKqOLJ+9Y5KkIgbtj2RHP3jpImDYtRkXemF4zu3K14r3zPHVusHefOYo4tun142Nl4r\n5kHclFfu7slTaP34ACRT+fWgmP+zd55xUVxdGD+zvbG7wNKrSBEBEUFFsddoxG7sii1qTDOJ\nSUxMLNEYE43Ja2IiahRbNBobxg4qNlCKFKU36X2X7W3m/QCBBRfYMpYk8//xgd29c2fm7uzc\nZ86957kPejnSNApJQ3l+XpUcrMfs2PYGDkOdbVBINVKRmmtNp5oXC8QwKMmW1pYqGGyyR6AF\ng2WK6JGK0OuHpGpVmyd+lQK7fkg6+3Mum2fcEW7bBt9/3+ad4mKYOBEyM8HZuYNtOkYpQ+P+\nqJGJm0VPbpI4bLKAb2fKyGD6LVnqDWnLS4lQe/P3xhHzeE5eRkfGZI3am78LVYrmFEiFDE2+\nKsZQ8O5rXIf2JEFTkKY/qTMvRZOdqPHpS9zWni/1laqHlxoUEi0AMC3I/cZb8W1NHHe++bu4\nJc9a0qB6mqka/ybX3gOfUezOQV6S+Zwq44exg1fHiSwDJryx3INScvv0n1tmXYrJvRW7LuiF\nzjAk+NdC3AH/ZVT8sSe6gTz056QbbzWtBrHp+8bM8z/t/O3SvZT4i0lCuRYFQDWYw8SD8acX\nupIBADau2jCo/8YUVujkIVj6zSM/ntWyBA4evcatXTqyxcYECX3/Q+TGySuR207INRhMcv9o\nhj85OylXAeA7eEDjw/jk+y25Egi75/TVU3zwHYitLZNn3K1BUYxCIwWPsmdzTb/1F6SKsx+K\nmv6vKVEMnmZnQsghJ1HVTtU1oVZhOYmqoJFGzNbCMPjf//S8L5HA3r2wcaOxhwZP7jW2qDoA\n0KiwRzeEw2bZGFuPVoM9vit79v30WzIThF3GbWmLqmsh7ZbEo7dxNsWZCepOPn0SrzZN2DXW\nK4qz6hksavcAgZm5mTKxKjupRqtBu/cSWNqa1VdjGOSl1jTWKxzcuY4e5j4qFT1pKMtvZHOp\nfqF2JudPYBgkXm5WdQAgF2uTrjSMnG9rQlVlOepn3XPunZVO/cB020XjeAlDsfk/LvkkTmg9\n6UDinxHuZABAN5ycF/LG7xsW75iSvM6PCDcTmM+/fxbUfxEyldY6oxnh+k76LPLc7YynNY0K\n9cNPugEA/43dR5tVHQCwgj7ZNEcAomTK3Bt51WKlStZQnp90+beN031be29O6PbopOJ6mRrF\nMAw7O48BANXV1QCQc+9Bvdvs3TdyqsWi0rTzG0Y7yJ/smTHrZ31JsbBq1SpEhz/++MPAcyrN\nbURRDAA0KrSiQE9+sOGU57eKFalII6rtTCh0RENlh1569R1/pJeaGqis1P9RerpRNbUcQPvO\nsrFWrdEnQztHXKfVu1V9hSkuaA2VetpZq8Yaa42rraGqM9e0Bv15Pl2Tn14rqlVUlYirS82y\nNgSAp9lCiUgpl6oLMurMrKqhSlZZLJaJ1fnpdWqVWfaNSpnmabZQq0Eb65UVhaafo0ykkYvb\nHIlEqJFLTDm2mhI9X72wWtsyveH5guC5Vqyhwb/k/b88UEHv1dubVB0AkOxnfPdpGEn7aE9k\nPDHljwAPCGH3L8Nh4uyhLNX1lX5BU9/e9OupnW9YIYj7R4ntSgUNGdImNy7h9J+1AKr4lMdG\n7Uxb1QgAWtTty7OHVw7zsuFwnQLC15+JWuQIkpvf/dJ+rwAALi4uwTpYWloauC9dSzAK1azr\ntl0en2lpfZ0EdchGxntoHQe/OvmoE549I4SEkIwP0HR0jiZU1UltxrZ/581LNnUQgkojN03O\no5htd0Khkf6u09wbbEtVZAqJRDarNhKF1GI4RzHjwPR+Xyb+iPR9WQgCZHO/AQPBEAS3PwN3\nWRQbWwjgNW6cp+67TuPG9QIojY3NeQ5nSfDfgxB2LxbFkQm6ASsyjW3l4j9s1qcHExs6uTOQ\nSCQAQFE9kQqtVttSAAAAur8dHX9k7WQv0bVf1q+c8cHJBoDKS8fv1upuRLGza2eKRUMAACSi\n5gFKTFJ058T3H8weFeLrajXtsBJAG7Pjo33xtW2PwJLLAADghU7poXMhsUdNHs0BKE5MbLPT\nJj799NNEHUaPHt3xabfBI4DP5FAAgGtNd/Yyy/TEI7B1c1tXhmlLitm6ddj5dPKRXvh88PPT\n/1FYmFE1NWPn3n4g2MaFbsLwooU1mcXVc4swLdlW71ZMCxJXYJwWs3Xt7K7V+aed4B1k6+LF\n9wq0ETiYm6Hp7mvl6MGzc7XwDjJ6+LsdXCuGTx8bezcLv1B7Yx8Y2kGlkXr2s7WyYzp78Rzc\nTf8FMThka8c2X6WNC53GMKXZnb31XBIO3al45dt2AQJAwu/PsEPOzs4GAB8fn7Zvd/P2pgLk\n5BDCjgAPCGH3MqD1mLB8+fLly9+MmDEmkF0ad2LbogGh71zvcPkhHo8HALW1eoRSTU0N/G1F\n14xFwNyvT94raGgoSry8tj8DQPVkx7jZ+0taS2iqqtqtT9Q04MbhNU/iKds3b/CsD3eefiTm\n+w7t50ICgLr4HcsGBk45UKij7bzdrQEAaOx2M2L4fB4AKBR4rg7E5lEHTHAaMs0lZLS9OfEG\nALB3Zw6eZucbyu8zyjp4jMC0SryDaRZWeg6Da03yDjZa93z1lZ43PT1h8WITDg18+nLsPVq1\nHc+G2nuEKdOzEAT6jmtve0ZlIEGjTJE+PQeyn9Vw/V7nGTuBPXAYtROT/97DTJx8SWOQ3XpY\n2bniYJRIoZK6B1h7B9kw2DgkAdi6WHj1tjF/dVcAsHZg+Q+09/C3MmetCAAIGWtp785oMih2\n6M4IHmNo3L0dVg7k4LFtUmeYFqRB017QWrEIAAnB7c/ABhWJGgHIPF67XxCJz7cAUAmFXfrJ\nExB0DZE88TJghr3366+jml9g9bGrB475MXv32r0fjvqwm77yvoGBVCh6fPt2A3i0vYVW3r6d\nB8AKDPR6ZiMK1y147Jje7K0JdCsQxZyNlSxZ+PcdMyUuTvLW5Nb7p7JCDQBkn6DmwBHNZcT7\nu798a85ILx4ZLkQw7kRpXntzXFLkhfNvf3Ri6p+zm1UCu183BuQqREXpatDJuaxPTy8HYHbr\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XFbEXnh7O3saqlSLixNS/h1gQNgSv68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5QJ+QOMo5uq9DtxRbjQ0AENNPGNLDPnGUqNO0W6ZBEIjobY9iCIohEb3tbcyAFtKD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\nl8xVKSJqceOF2aosK0yXV8cxwm7SNK168nNfB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wDIPjnGE0DdWbpbvDg+I3cUE1O8MJfLXr14IYTyycX9m1f+vGDRL+F/HL+RzDuzy0zt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\nnbQ3/i1jjGUnnV3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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dplot <- DotPlot(condsobj, features = hmapGenes, group.by = \"ct_cond\") + RotatedAxis() + coord_flip() + ggtitle(p)\n",
    "dplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b3d2b0b5-1408-4d19-a947-96410b4c7c11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Rbm11</th><td>0.07057051</td><td> 3.2907038</td><td>Rbm11 </td><td>GABAergic_2N_old</td><td>-0.1898698</td></tr>\n",
       "\t<tr><th scope=row>Hspa13</th><td>0.25474080</td><td>10.3283225</td><td>Hspa13</td><td>GABAergic_2N_old</td><td> 0.4708921</td></tr>\n",
       "\t<tr><th scope=row>Samsn1</th><td>0.01174252</td><td> 0.2542817</td><td>Samsn1</td><td>GABAergic_2N_old</td><td>-0.3725276</td></tr>\n",
       "\t<tr><th scope=row>Nrip1</th><td>1.35895002</td><td>15.8103358</td><td>Nrip1 </td><td>GABAergic_2N_old</td><td>-0.2987784</td></tr>\n",
       "\t<tr><th scope=row>Usp25</th><td>1.48396688</td><td>19.9012789</td><td>Usp25 </td><td>GABAergic_2N_old</td><td>-0.4301870</td></tr>\n",
       "\t<tr><th scope=row>Cxadr</th><td>0.78166649</td><td>17.0967018</td><td>Cxadr </td><td>GABAergic_2N_old</td><td> 0.5141773</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tRbm11 & 0.07057051 &  3.2907038 & Rbm11  & GABAergic\\_2N\\_old & -0.1898698\\\\\n",
       "\tHspa13 & 0.25474080 & 10.3283225 & Hspa13 & GABAergic\\_2N\\_old &  0.4708921\\\\\n",
       "\tSamsn1 & 0.01174252 &  0.2542817 & Samsn1 & GABAergic\\_2N\\_old & -0.3725276\\\\\n",
       "\tNrip1 & 1.35895002 & 15.8103358 & Nrip1  & GABAergic\\_2N\\_old & -0.2987784\\\\\n",
       "\tUsp25 & 1.48396688 & 19.9012789 & Usp25  & GABAergic\\_2N\\_old & -0.4301870\\\\\n",
       "\tCxadr & 0.78166649 & 17.0967018 & Cxadr  & GABAergic\\_2N\\_old &  0.5141773\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Rbm11 | 0.07057051 |  3.2907038 | Rbm11  | GABAergic_2N_old | -0.1898698 |\n",
       "| Hspa13 | 0.25474080 | 10.3283225 | Hspa13 | GABAergic_2N_old |  0.4708921 |\n",
       "| Samsn1 | 0.01174252 |  0.2542817 | Samsn1 | GABAergic_2N_old | -0.3725276 |\n",
       "| Nrip1 | 1.35895002 | 15.8103358 | Nrip1  | GABAergic_2N_old | -0.2987784 |\n",
       "| Usp25 | 1.48396688 | 19.9012789 | Usp25  | GABAergic_2N_old | -0.4301870 |\n",
       "| Cxadr | 0.78166649 | 17.0967018 | Cxadr  | GABAergic_2N_old |  0.5141773 |\n",
       "\n"
      ],
      "text/plain": [
       "       avg.exp    pct.exp    features.plot id               avg.exp.scaled\n",
       "Rbm11  0.07057051  3.2907038 Rbm11         GABAergic_2N_old -0.1898698    \n",
       "Hspa13 0.25474080 10.3283225 Hspa13        GABAergic_2N_old  0.4708921    \n",
       "Samsn1 0.01174252  0.2542817 Samsn1        GABAergic_2N_old -0.3725276    \n",
       "Nrip1  1.35895002 15.8103358 Nrip1         GABAergic_2N_old -0.2987784    \n",
       "Usp25  1.48396688 19.9012789 Usp25         GABAergic_2N_old -0.4301870    \n",
       "Cxadr  0.78166649 17.0967018 Cxadr         GABAergic_2N_old  0.5141773    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(dplot$data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b75733cf-3a45-4ee4-9ad2-b133d50ce8a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "100"
      ],
      "text/latex": [
       "100"
      ],
      "text/markdown": [
       "100"
      ],
      "text/plain": [
       "[1] 100"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "0"
      ],
      "text/latex": [
       "0"
      ],
      "text/markdown": [
       "0"
      ],
      "text/plain": [
       "[1] 0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "max(dplot$data$pct.exp)\n",
    "min(dplot$data$pct.exp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "35454d81-83dd-4396-83d7-da66070bda84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "100"
      ],
      "text/latex": [
       "100"
      ],
      "text/markdown": [
       "100"
      ],
      "text/plain": [
       "[1] 100"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 1 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>avg.exp</th><th scope=col>pct.exp</th><th scope=col>features.plot</th><th scope=col>id</th><th scope=col>avg.exp.scaled</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Ttc310</th><td>281833401658</td><td>100</td><td>Ttc3</td><td>BFCN_2N_yng</td><td>0.2082039</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 1 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & avg.exp & pct.exp & features.plot & id & avg.exp.scaled\\\\\n",
       "  & <dbl> & <dbl> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\tTtc310 & 281833401658 & 100 & Ttc3 & BFCN\\_2N\\_yng & 0.2082039\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 1 × 5\n",
       "\n",
       "| <!--/--> | avg.exp &lt;dbl&gt; | pct.exp &lt;dbl&gt; | features.plot &lt;fct&gt; | id &lt;fct&gt; | avg.exp.scaled &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| Ttc310 | 281833401658 | 100 | Ttc3 | BFCN_2N_yng | 0.2082039 |\n",
       "\n"
      ],
      "text/plain": [
       "       avg.exp      pct.exp features.plot id          avg.exp.scaled\n",
       "Ttc310 281833401658 100     Ttc3          BFCN_2N_yng 0.2082039     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data <- dplot$data\n",
    "max(data$pct.exp)\n",
    "\n",
    "data[which(data$pct.exp == 100),]"
   ]
  }
 ],
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