WGCNA分析（四）基因与性状关系（GS）& 基因与模块关系（M

计算 module membership (MM): 基因与模块的相关性

每一条基因与模块的相关性

 geneModuleMembership = as.data.frame(cor(Texp0, MEs, use = "p"))

  MMPvalue = as.data.frame(corPvalueStudent(as.matrix(geneModuleMembership), 
                                            nsamples))

  names(geneModuleMembership) = paste("MM", modNames, sep="")

  names(MMPvalue) = paste("p.MM", modNames, sep="")

计算 Gene Significance (GS): 基因与性状的相关性

每一条基因与形状的相关性，重点关注相关性高的基因

geneTraitSignificance = as.data.frame(cor(Texp0, datTraits, use = "p"))

  GSPvalue = as.data.frame(corPvalueStudent(as.matrix(geneTraitSignificance), 
                                            nsamples))

  names(geneTraitSignificance) = paste("GS.", traitNames, sep="");

  names(GSPvalue) = paste("p.GS.", traitNames, sep="");

  geneInfo<-cbind(geneModuleMembership, MMPvalue, geneTraitSignificance, GSPvalue)

  write.table(geneInfo, file = "geneInfo.txt", 
              sep = "\t", 
              quote = F)