Dear Bioconductor users,
I am using WGCNA software for RNA-seq data (320 patient samples) and I want to decipher potential mechanisms underlying hepatocellular carcinoma progression. First, I removed all features that have a count of less than 10 in more than 90% of the samples and I transformed my data using varianceStabilizingTransformation function implemented in DEseq2 package. Second, I removed all potential outliers and then I used the pickSoftThreshold function to select the beta power for signed network construction. As you can see in the attached plot, the SFT fit index of power of 12 (default option) fails to reach the 0.8. The power of 16 fits the Scale free topology. Although the power of 16 means network modules with low mean connectivity. Which is your opinion about the selection of soft threshold power in my case? Is it absolutely necessary the selection of the soft threshold power based in SFT criterion?
Thank you for your time in advance!!