I've been calculating differential expression for two separate groups both of which have baseline and treatment expression measurements. I have looked at differential expression between the baseline and treatment and now have 2 lists of differentially expressed genes. Differentially expressed genes were identified with edgeR with appropriate correction for FDR.

It's an interesting question to compare the lists of differentially expressed genes and I can identify genes significantly up- and down-regulated in both groups. I can also show that the overlap in these lists is significant using Fisher's exact test.

However, when I look at genes that are significantly differentially expressed in only one group do I need to do any further analysis or test to ensure the difference is "real"? For example, one gene could be significantly DE in one group close to the cutoff for significant (e.g. P = 0.049) but just misses the cutoff in the second group (e.g. P = 0.051). I've been unable to find anything about this online so far.




I'd encourage you to use GSEA or a similar rank-based method for comparisons rather than choosing some p-value cut-off and comparing lists.