Hi all,

I'm using interaction terms for DGE analysis I'm doing using DESeq2. I have a case and control group (SA and CTRL, respectively) and males and females per group (Male, Female). I would like investigate sex differences between cases and controls. Here is the design formula:

dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~  Age_scale + pH_scale + Sex + Group + Sex:Group

However, I'm having trouble truly understanding what goes on when obtaining results in the presence/absence of using contrast=list(c(.

To explain myself more clearly, what is the difference between:

1) Using no specified contrast when obtaining results. I understand that DESeq2 takes by default the last term, so, you have the results of the interaction effect alone. It is my understanding that what is happening here is: group effect in the female group - the group effect in the male group (group effect is SA vs CTRL). (Male and CTRL as references).

2) Using for example contrast=list( c("Group_SA_vs_CTRL", "SexFemale.GroupSA"))) when obtaining results.

In my mind, 2 is identical to 1. But is that actually true? Can someone explain to me the precise steps/differences in how results are determined, if there are any?

Thanks!

There is a section on interactions in the vignette, but if you want to know more, I recommend to work with someone familiar with linear models in R.

Also ?results has a lot of information about how the tables can be printed, e.g. the different ways to use contrast.