I ran WGCNA for my genes following the tutorials by Horvath and Langfelder (https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/). I've obtained my modules and the GS and MM for my list of genes - however I think my situation is a bit odd. I've read in a few papers that to identify hub genes, one can use cut offs of absolute values of GS > 0.2, and MM > 0.8.
In my case, after implementing those cutoffs, nothing remains. All my genes had GS values JUST under 0.2, and MM just under 0.8. I am very confused and interested in this result - I don't know what this means. There were clearly modules with high significance (correlations were weak, about 0.3-0.7, but p values were quite significant <0.000001).
Is the inability to find hub genes because my modules happen to have weak correlations with the traits of interest that I am testing? This is my only reasoning thus far as obviously no paper is going to talk about NOT finding any hub genes...
Anyone aware of any other cutoffs papers have used? It seems that GS > 0.2, and MM > 0.8 is the standard but I think I remember reading a paper that only used GS > 0.2 although I can't seem to find it anymore.