I've been tasked with looking at DE genes in a scRNA-seq dataset. It's a timecourse experiment with three timepoints (3, 6 & 12 hrs) with a control and treatment at each time. There was an issue with the 3hr control cells and they are not being used. I clustered the cells and identified that all of the 6 and 12 hr cells cluster together and the 3hr cells cluster together separately.
What I'm trying to look at now is the difference between the two clusters taking into consideration the control cells.
So, a design like this:
3hr treatment - ((12 treatment - 12 control) + (6 treatment - 6 control))
Here is the code:
design <- model.matrix(~0+ group) # groups have been set up like this: group_12T, group_12C, group_6T etc dge <- estimateDisp(dge, design = design) fit <- glmFit(dge, design) con <- makeContrasts(group_3T-((group_12T - group_12C)+(group_6T - group_6C)), levels=design) con
Contrasts Levels group_3T - ((group_12T - group_12C) + (group_6T - group_6C)) group_12T -1 group_12C 1 group_3T 1 group_6T -1 group_6C 1
fit = glmLRT(fit, contrast = con)
When I set this up and run it, the results are somewhat unusual biologically speaking.
My question is, have I made any mistakes with my process above? or is there a more suitable process of events I should be following?
Thanks in advance!