I'm working on DEG dataset and I've done Pearson correlation to prepare my dataset for downstream analysis (co-expression network), so this isn't an exploration phase. When I do pearson on R using Hmisc I get P and R values. I'm trying to use these p-values to make sure that the correlation value r is significant, but since I don't know anyway to correct for pearson bias, I went with p.adjust.
I will attach 3 images 1 for the native p-values, BY-adjusted p.values, and BH-adjusted p.values. Looking at BH and native, I don't think BH adjusted anything, the curve is still showing perfect gradual decrease from 1 to 0, there are no adjusted p.values. While with BY, there is a noticeable new curve at 1 showing the adjusted values that were probably considered significant earlier.
The reason why I originally wanted to go with BY is because it assumes that the two correlated variables regulate or dependent on each other, which fits this biological concept.
Is my reasoning correct?
I tried reading about the expected plots for p-values, and other stackoverflow prior questions about this, unfortunately non-exactly addressed my question. I would love to get a more tailored response to my case in this question.
Thank you.
