I've looked at a number of posts on multiple treatment comparisons, but couldn't find an example of this exact situation. I'm looking at RNA expression in two cell types WT and KO. For each cell type I have 5 different treatment conditions: Mock, A, B, C, D.
Cell Treatment WT mock WT mock WT mock WT A WT A WT A WT B WT B WT B WT C WT C WT C WT D WT D WT D KO mock KO mock KO mock KO A KO A KO A KO B KO B KO B KO C KO C KO C KO D KO D KO D
First I'd like to ask is there a difference in expression between any of the treatment conditions (mock, A, B, C, D) within a cell type. Looking at some other forum posts, it looks like people recommend just grouping them and then using contrasts to compare everything to mock. Is this the best method?
dds$group <- factor(paste0(dds$Cell, dds$Treatment)) design(dds) <- ~ group results(dds, contrast=c('group', 'AWT', 'MOCKWT') results(dds, contrast=c('group', 'BWT', 'MOCKWT') results(dds, contrast=c('group', 'CWT', 'MOCKWT') results(dds, contrast=c('group', 'DWT', 'MOCKWT')
However, next I would like to ask whether there is a difference in treatment vs mock comparing the WT and KO cells. Essentially, is there a difference in the genes that change between A vs mock in WT and A vs mock in KO, B vs mock in WT and B vs mock in KO, etc. I think I would need to rewrite the design model with an interaction term, but I'm not quite sure what it would look like. Any suggestions would be greatly appreciated.