Which module to select for Pathway analysis based on Module trait correlation and pvalue? I have a total of 35 tumor samples classified into 4 subtypes. Subtype A, B, C, and D. I have RNAseq data. I'm interested in identifying modules related to each subtype with co-expression network analysis. I have read the WGCNA tutorial and create a trait.csv file like below:

Showing here some rows of the trait.csv file.



SamInfo &lt;- read.csv("trait.csv")

Samples = rownames(datExpr);
traitRows = match(Samples, SamInfo$Samples);
datTraits = SamInfo[traitRows, -1];
rownames(datTraits) = SamInfo[traitRows, 1];

nGenes = ncol(datExpr);
#15648L

nSamples = nrow(datExpr);
#35L

#calculate eigengenes (1st principal component) of modules
MEs0 = moduleEigengenes(datExpr, dynamicColors)$eigengenes
MEs = orderMEs(MEs0)
moduleTraitCor = cor(MEs, datTraits, use = "p");
moduleTraitPvalue = corPvalueStudent(moduleTraitCor, nSamples);

#Will display correlations and their p-values
textMatrix = paste(signif(moduleTraitCor, 2), "\n(", signif(moduleTraitPvalue, 1), ")", 
                   sep = "");
dim(textMatrix) = dim(moduleTraitCor)
par(mar = c(6, 8.5, 3, 3));

#Display the correlation values within a heatmap plot
labeledHeatmap(Matrix = moduleTraitCor, xLabels = names(datTraits), 
               yLabels = names(MEs), ySymbols = names(MEs), colorLabels = FALSE, 
               colors = blueWhiteRed(50), textMatrix = textMatrix, setStdMargins = FALSE, 
               cex.text = 0.5, zlim = c(-1,1), main = paste("Module-trait relationships"))


The Correlation between Subtypes and Modules Heatmap looks like below:



For functions identification (Pathway Analysis), from the above output for each subtype, should I select only the modules that were significantly positively correlated with subtypes, or Can I also use the significantly negatively correlated modules?

Is it good to use the modules that were not significant for pathway analysis?

In case if I can use positive and negative correlated modules, Can I combine those modules and use those genes for Pathway analysis?
If you can run pathway analysis programmatically on all modules, yes, do it on all modules. Otherwise, select the modules with strongest associations with each subtype, both positive and negative. I would keep the modules separate because they may have very different biological functions.