Hi there,

I'm using WGCNA to construct co-expression network. My input is z-score normalized expression from RNAseq. Here is the distribution of normalized expression cross samples: https://ibb.co/Mf5zC0w

And here is how the soft threshold - scale independence plot looks like https://ibb.co/tbHx3MV

This is my codes:

powers = c(seq(1,10,by = 1), seq(12, 30, by = 2))
sft = pickSoftThreshold(datExpr, powerVector = powers, verbose = 5)

par(mfrow = c(1,2));
cex1 = 0.9;
plot(sft$fitIndices[,1], -sign(sft$fitIndices[,3])*sft$fitIndices[,2],
         xlab="Soft Threshold (power)",ylab="Scale Free Topology Model Fit,signed R^2",type="n",
         main = paste("Scale independence"));
text(sft$fitIndices[,1], -sign(sft$fitIndices[,3])*sft$fitIndices[,2],
         labels=powers,cex=cex1,col="red");
 abline(h=0.90,col="red")
 plot(sft$fitIndices[,1], sft$fitIndices[,5],
         xlab="Soft Threshold (power)",ylab="Mean Connectivity", type="n",
         main = paste("Mean connectivity"))
 text(sft$fitIndices[,1], sft$fitIndices[,5], labels=powers, cex=cex1,col="red")

My question is why the soft threshold - scale independence looks so weird?