We are trying to identify fst outliers from a comparison of two populations. We've settled on using pFst from the GPAT++ package.
To my reading, in such studies folks sometimes use bonferonni or benjami-hochberg-corrected p values. In other cases, I've seen arbitrary cutoffs like 10-8. I'm wondering if anyone has suggestions about best practices?
I also notice that GPAT has a permutation test to derive empirical p values, and that seems desirable, but it is not totally clear from the documentation what this is doing. It would seem like in pFst itself, we could shuffle population assignment to get a null distribution of pFst. but I wonder if this is redundant with what pFst is already doing...
Thanks for any feedback/suggestions you might have!