I know WGCNA is not hosted here. But I have a very general question about WGCNA:
One critical step in WGCNA pipeline is to calculate the correlation between eigen-genes and traits. Besides the correlation, we also calculate a p value for each correlation using
corPvalueStudent(). I thought that’s a typical multiple hypothesis testing problem since we are testing many traits against many eigen-genes. Now the question is: should we adjust the p-value?
I didn’t see many people discussing this, although WGCNA is a very popular software. Even in the official tutorial, they are using the un-adjusted p-value. Isn't this problematic?