I have recently used the WGCNA for a whole brain imaging experiment and it seems to have worked well, but I have a question. First some background: The experiment consisted of imaging whole brain samples(n=20) which were stained with c-fos (a marker of neural activity). So I have a 20x300 matrix with each column representing the number of activated cells in said brain region. I can achieve a scale free topology with a power of 7 or higher and I get a decent number of modules (4-6 depending on the minmodule size) which make sense biologically and correlate (as high as .75) with my trait of interest. However, I did not filter out any regions with the exception of regions with mostly 0 cells activated. My questions is should I filter out regions and if so, how? I've seen some remove the mean/median for each gene (in my case brain region) but I have also seen filtering out genes with low variance. If I use one of these techniques should I do it before or after I log transform my data?