A question was posed to me by a colleague today, and I'm not entirely sure I have a good answer. For my own knowledge and for the benefit of my colleague, I'd like to know what you'd do to address their specific proposal. I have a few of my own ideas about how one could do this, but I'm not super confident in their technical "correctness".
You have 3 tables of DESeq2 results. Each table represents a contrast between the same treatment and control (no treatment), but in a different cell line. You'd like to aggregate these changes to identify changes that are consistent across each cell line. You'd also like to use this aggregate data for use in a downstream geneset enrichment analysis to identify biological processes associated with the treatment, so you'll need some way of ranking the genes. In this scenario, how would you aggregate the gene expression changes/pvalues across the three contrasts, and what calculated statistic should you use to rank the consensus genes?