先碼
WGCNA代碼1：WGCNA分析遗座，簡單全面的最新教程
WGCNA代碼2：WGCNA實戰(zhàn)練習+離群點+隨機選取基因TOM作圖
含有離群點
clust = cutreeStatic(
sampleTree,
cutHeight = 15,
minSize = 10)
keepSamples = (clust==1)
datExpr = datExpr0[keepSamples, ]
nGenes = ncol(datExpr)
nSamples = nrow(datExpr)
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原文鏈接：https://blog.csdn.net/weixin_43569478/article/details/83747303
nSelect = 400
# For reproducibility, we set the random seed
set.seed(10);
select = sample(nGenes, size = nSelect);
selectTOM = dissTOM[select, select];
# There’s no simple way of restricting a clustering tree to a subset of genes, so we must re-cluster.
selectTree = hclust(as.dist(selectTOM), method = "average")
selectColors = moduleColors[select];
# Open a graphical window
sizeGrWindow(9,9)
# Taking the dissimilarity to a power, say 10, makes the plot more informative by effectively changing
# the color palette; setting the diagonal to NA also improves the clarity of the plot
plotDiss = selectTOM^7;
diag(plotDiss) = NA;
TOMplot(plotDiss, selectTree, selectColors, main = "Network heatmap plot, selected genes")
WGCNA代碼3：WGCNA相關性分析+模塊和性狀
WGCNA代碼4：WGCNA實例分析及解讀+檢驗選定的β值下記憶網(wǎng)絡是否逼近 scale free+hub gene
k <- softConnectivity(dataExpr,power=sft$powerEstimate)
sizeGrWindow(10, 5)
par(mfrow=c(1,2))
hist(k)
scaleFreePlot(k,main="Check Scale free topology\n")
#可以看出k與p(k)成負相關(相關性系數(shù)0.87),說明選擇的β值能夠建立基因無尺度網(wǎng)絡
k
根據(jù)性狀與模塊特征向量基因的相關性及pvalue來挖掘與性狀相關的模塊
cor_ADR <- signif(WGCNA::cor(traitData,MEs,use="p",method="pearson"),5)
p.values <- corPvalueStudent(cor_ADR,nSamples=nrow(traitData))
Freq_MS_max_cor <- which.max(abs(cor_ADR["Insulin_ug_l",-which(colnames(cor_ADR) == "MEgrey")]))
Freq_MS_max_p <- which.min(p.values["Insulin_ug_l",-which(colnames(p.values) == "MEgrey")])
根據(jù)基因網(wǎng)絡顯著性油湖，也就是性狀與每個基因表達量相關性在各個模塊的均值作為該性狀在該模塊的顯著性齐莲，顯著性最大的那個模塊與該性狀最相關：
GS1 <- as.numeric(WGCNA::cor(traitData[,'Insulin_ug_l'],dataExpr,use="p",method="pearson"))
GeneSignificance <- abs(GS1)
ModuleSignificance <- tapply(GeneSignificance,net$colors,mean,na.rm=T)
尋找與該性狀相關的樞紐基因（hub genes）,首先計算基因的內部連接度和模塊身份嚣鄙，內部連接度衡量的是基因在模塊內部的地位，而模塊身份表明基因屬于哪個模塊鳍怨。
WGCNA代碼5：小張聊科研
