## Example: first simulate some data.
MEturquoise = sample(1:100,50)
MEblue = sample(1:100,50)
MEbrown = sample(1:100,50)
MEyellow = sample(1:100,50)
MEgreen = c(MEyellow[1:30], sample(1:100,20))
MEred = c(MEbrown [1:20], sample(1:100,30))
MEblack = c(MEblue [1:25], sample(1:100,25))
ME = data.frame(MEturquoise, MEblue, MEbrown, MEyellow, MEgreen, MEred, MEblack)
dat1 = simulateDatExpr(ME,300,c(0.2,0.1,0.08,0.051,0.05,0.042,0.041,0.3),
signed=TRUE)
TOM1 = TOMsimilarityFromExpr(dat1$datExpr, networkType="signed")
colnames(TOM1) <- rownames(TOM1) <- colnames(dat1$datExpr)
tree1 <- tree2 <- fastcluster::hclust(as.dist(1-TOM1),method="average")
colorh = labels2colors(dat1$allLabels)
hubs = chooseOneHubInEachModule(dat1$datExpr, colorh)
hubs
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