Hi,

I am trying to build a weighted network using WGCNA. While reading their paper (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-559#Sec1), I found they have used TOM for interconnectedness calculation. When I checked the TOM paper (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-8-22) I found that generalised TOM worked better than TOM for the unweighted network. I was just wondering if there is a way I can apply GTOM on my weighted network? Has anyone done it before? If yes, does it perform better for the weighted network as well? Is there some example code on how to implement that within WGCNA. Thanks very much for the help.

Nurun

Well, not many people (actually no one I know, but I don't know that many people) seem to be using GTOM. You could take code from the old tutorials at https://horvath.genetics.ucla.edu/html/GTOM/ and use it with WGCNA along the lines of tutorial I, section 2b ("manual" network construction and module identification) where you would replace the standard TOM calculation by the GTOM calculation as described in the GTOM tutorials. Whether it is better is probably still an open question.

Istvan Kovacs at Northwestern has done some research on this topic and I believe also has some suggestions/guidelines to improve the usual TOM. Unfortunately, apart from hearing him give a talk I have not had time to study his papers/results and recommendations.