WGCNA分析(五)网络可视化

2023-07-20  本文已影响0人  Bioinfor生信云

基因共表达网络可视化

计算 dissTOM, dissTOM = 1 - TOM

dissTOM = 1-TOMsimilarityFromExpr(Texp0, power = x$powerEstimate);

取 10次方,仅为展示更显著

  plotTOM = dissTOM^10

绘图

diag(plotTOM) = NA;
  sizeGrWindow(9,9)
  geneTree = net$dendrograms[[1]]
  TOMplot(plotTOM, geneTree, moduleColors, main = "Network heatmap plot, all genes")

模块特征向量网络可视化

# 重新计算MEs
  MEs = moduleEigengenes(Texp0, moduleColors)$eigengenes

和性状之间的关系图

  sizeGrWindow(5,7.5)
  par(cex = 0.9)
  plotEigengeneNetworks(MEs, "", marDendro = c(0,4,1,2), marHeatmap = c(3,4,1,2), cex.lab = 0.8, xLabelsAngle
                        = 90)

绘制树状图

  sizeGrWindow(6,6)
  par(cex = 1.0)
  plotEigengeneNetworks(MEs, "Eigengene dendrogram", marDendro = c(0,4,2,0),
                        plotHeatmaps = FALSE)

绘制热图矩阵

  par(cex = 1.0)
  plotEigengeneNetworks(MEs, "Eigengene adjacency heatmap", marHeatmap = c(3,4,2,2),
                        plotDendrograms = FALSE, xLabelsAngle = 90)
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