Calculation of module membership in WGCNA
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ag1805x ▴ 50
@ag1805x-15215
Last seen 1 day ago
University of Allahabad

What is the difference between the following two chunks of code?

geneModuleMembership = as.data.frame(cor(datExpr, MEs, use = "p"));
MMPvalue = as.data.frame(corPvalueStudent(as.matrix(geneModuleMembership), nSamples));
geneTraitSignificance = as.data.frame(cor(datExpr, weight, use = "p"));
GSPvalue = as.data.frame(corPvalueStudent(as.matrix(geneTraitSignificance), nSamples));

and

datKME = signedKME(datExpr, MEs, outputColumnName = "kME")

The first chunk is to calculate Gene Significance GS (the absolute value of the correlation between the gene and the trait) and module membership MM (the correlation of the module eigengene and the gene expression profile). While in the second, the signedKME is used for calculation of (signed) eigengene-based connectivity, also known as module membership.

Is there any difference between them in calculation of module membership? Which one should be used and in what scenario? For hub gene selection, which is better - kME, GS or MM?

WGCNA RNA-seq ModuleMembership Network Hub gene • 858 views
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@peter-langfelder-4469
Last seen 12 months ago
United States

signedKME does a lot of checks but it essentially also simply calculates the correlation (not the p-values). You need to use kME or MM (should be the same) for hub gene selection. GS measures association with trait, not module membership or hubgene status.

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