WGCNA分析（三）模块与性状关联分析

导入性状数据

  traits <- read.delim("traits.txt", row.names=1)

  # 保证traits与 Texp0 矩阵的 rownames 顺序一致
  rownames(traits)
  traitrows = match(rownames(Texp0), rownames(traits))
  traits = traits[traitrows, ]

模块与性状关系

统计样本数目和基因数目

  ngenes = ncol(Texp0)
  nsamples = nrow(Texp0)

计算模块特征向量 MEs

  MEs0 = moduleEigengenes(Texp0, moduleColors)$eigengenes
  MEs = orderMEs(MEs0)

MEs与性状之间的相关性

  moduleTraitCor = cor(MEs, traits, use = "p")
  moduleTraitPvalue = corPvalueStudent(moduleTraitCor, nsamples)

heatmap绘图

  ## 连接相关性和 pvalue
  textMatrix = paste(signif(moduleTraitCor, 2), "\n(",
                     signif(moduleTraitPvalue, 1), ")", sep = "");
  dim(textMatrix) = dim(moduleTraitCor)
  
  
  ## heatmap 画图
  labeledHeatmap(Matrix = moduleTraitCor,
                 xLabels = names(rraits),
                 yLabels = names(MEs),
                 ySymbols = names(MEs),
                 colorLabels = FALSE,
                 colors = greenWhiteRed(50),
                 textMatrix = textMatrix,
                 setStdMargins = FALSE,
                 cex.text = 0.5,
                 zlim = c(-1,1),
                 main = paste("Module-trait relationships"))