Hello! Here are the powerpoints for both FF lesion and Aging Projects.
This directory also contains everything we discussed during our meeting on 1/9/24. When I come back from my trip I'll reorganize these updated files and move the older files away.

FF lesion: https://docs.google.com/presentation/d/18E4trlzFXbqPKtgj2zpOqkio2adMKFj4oR2FergZNik/edit#slide=id.g2ad71970d6a_0_0
Annotation begins on slide 60

Aging: https://docs.google.com/presentation/d/1riqVSyEwe2Hsx1Z6iDyf7iE8VK0blT-CcbZWIuqb9xg/edit#slide=id.g2ad7fb0d3b1_0_5
Annotation begins on slide 41

Both RDS files with v1 of annotations are located here:
https://epigenomics.sdsc.edu/kdang/ASAP_proj/post_annotationV1_RDS/

Also, even though I won't have my laptop with me I won't be completely off the grid :)
So please email me if you can't access the powerpoint(s) or can't find certain files.
See you in two weeks!!

Here is a breakdown of the directory post_annotationV1:
### Aging: ###
* Aging_geneExp_acrossCelltypes
	- average expression of Tri16 genes across celltypes
	- input used for anova test
	- csv_out/: input for anova test; average expression of Tri16 genes across datasets
	- csv_out_sorted/: same thing as above, but sorted datasets to match 2N_yng, 2N_old, Dp16_yng, Dp16_old (these can be used to make anova plots)
	- Tri16_avgExp_acrossCelltypes_aovReport.txt: written report of aovSummary
	- Tri16_avgExp_acrossCelltypes_aovSummary.pdf: anova tests were ran on each average expression across datasets file for each celltype. This pdf contains tables of the anova test results
* DESeq2_OUT
	- DESeq2 run across celltypes
	- using just conditions as a variate (formula: ~conditions)
	- aka "default run of DESeq2"
* DESeq2_interactions_OUT
	- same as above BUT using age and genotype as covariates
	- using DESeq2 "interactions" feature
	- formula: ~genotype + age + genotype:age
	- note: I may need revisit since the countSummary file doesn't appear to have applied the formula
* FM.report_Aging_LabelTransfer
    - Find Markers report for aging across seuarat clusters
    - please note that this was running before I completed version 1 of annotation, so the results are shown for cluster numbers. However, each cluster has it's own label so essentially cluster 0 would be oligo for example.
* bulkMatrices
	- bulkmatrices (gene x datasets) one per celltype
	- input for DESeq2
* genelist_dotplots
	- row normalized dotplots of genelists: apoptosis, cell cycle regulation, Ptbp1 regulation, cGAS STING, sanity genelist (the one Allen mentioned at 1/9 meeting)
* Aging_AnnoV1_UMAP.pdf
	- UMAPs of annotations v1 and seurat cluster numbers

### FFlesion ###
* FM.report_FFlesion_annV1
	- Find Markers report of FF lesion across celltypes
* genelist_dotplots
	- same as above
* FFlesion_AnnoV1_UMAP.pdf
	- same as above
    
### FFlesion_Aging_anno_KD.xlsx ###
* fflesion sheet goes over my thought process on annotations
    - if label transfer (LT) and MapMyCells (MMC) matched labels then I was fairly confident in annotating that
    - otherwise, featureplots and scCustom dotplot were used to annotate
* FFLESION_CURRENT_ANNO
    - current annotations for ff lesion v1
* aging sheet is the same process and format as fflesion above
* AGING_CURRENT_ANNO
    - current anootations for aging v1
    - THIS IS IMPORTANT: USE THIS WHEN REFERENCING "FM.report_Aging_LabelTransfer" (EX: CLUSTER 0 = OLIGO) :P