WGCNA, analysis on two data sets

Question

[halehashki]

Hello, I have two healthy and cancer data sets and want to do WGCNA analysis. My goal is to detect the genes that are significant/different in these two data sets comparing to each other. My questions is should I follow the second part (II. Consensus analysis of female and male liver expression data) in this page: https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/

Or the third tutorial also consider the traits in calculation? I didn't see anything related to traits identifying in Adjacency and TOM calculation. But gene significance calculation get the traits information. So I am confused how the traits information is been considered in analysis. I will be thankful if you advice me what is the best way to use WGCNA for two data sets analysis.

Thanks, Haleh

Answer 1

[WouterDeCoster]

Please read question 1 of the FAQ: https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/faq.html

TLDR: you don't have enough samples

[halehashki]

Thank you for your response. I think my question wasn't clear. I have more than 20 samples, having two conditions (HC vs Non-HC). My question is when I have data sets of two conditions, how to use WGCNA that consider the condition in correlation calculation. What I see, even in Male and Female liver example, they do the analysis separately and then get the consensus one. Here I am not looking for consensus, I am looking for differences.

I will be thankful is someone can help me out. Thanks

[Francelly]

Hello, how is everything? Have you had any opinions on this issue? If yes, you could share the information with me, because I am having the same problem.

Thank you