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WGCNA Soft Power Problem

Hello,

As a newbie I was trying to do WGCNA for my transcriptomics data. I used vst normalization and tried to choose soft power. Even in high numbers I couldn't reach 0.8 threshold. Is there any suggestions for overcome this problem?

enter image description here

normalization wgcna rna-seq deseq2
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updated by LChart LChart • written by Ömür Koray • Ömür Koray

Have you performed any sample filtering or gene filtering? I would (1) check the top few PCs for outlier samples, and exclude; (2) Proceed with WGCNA at a moderate power (12-16) and inspect the dendrogram, looking for tiny gene clusters (2-4 genes) with very strong/outlier linkage, and investigate whether those should be retained.

If you have a very strong gene expression driver (say you're looking at cell lines or treatments), then you may prefer to use truncated R2 in place of R2.

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written by LChart LChart

Thanks for your reply. I have tried without filtering & filtering out low counts with (rowMeans > 0, 5, 10) but soft power threshold graph remains kind of same. Regarding to your first approach since I have low number of samples (6) and i just have age variable between my samples, no treatment. I am also attaching my PCA plot.

enter image description here

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written by Ömür Koray • Ömür Koray

n=6 is very low for WGCNA. The general advice would be to set softPower to something like 12-16 and see what comes out.

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written by LChart LChart

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