I have got two sets of differentially expressed genes derived from comparing two treatments to a single control baseline, i.e Treat1 – Ctrl and Treat2 – Ctrl.
My objective is to discuss the genes common to both treatments, and the genes differentially expressed in specific treatments. Currently I've done this in a very simple way, just by calculating the intersections and differences of the DEGs. It's quite clear that the DEG lists are sensitive to the arbitrary thresholds set (p < 0.05, FC > 1.5) and there are many cases where I'm saying a gene is specific to Treat1 where the fold changes are extremely close i.e., Treat1 FC = 1.6, Treat2 FC = 1.4.
I feel like there has to be a better way than this, does anyone have any suggestions or ideas?