Question: WGCNA defining parameters for soft threshold in R?
0
gravatar for madkitty
4.6 years ago by
madkitty590
Canada
madkitty590 wrote:

I'm trying to compare 3 "control" datasets to 2 different samples in WGCNA. I have no clue about standards to run WGCNA nor do I understand why people use that stuff.. anyhow my boss wants to me to use it.  When following the steps posted here: 

http://pklab.med.harvard.edu/scw2014/WGCNA.html

Apparently, we need to define a soft threshold, and I don't understand how can I determine necessary parameters. Is there any rule to help me pick up the parameters cex1, abline h and the soft power threshold? 

powers = c(c(1:10), seq(from = 12, to=20, by=2)); sft=pickSoftThreshold(datExpr,dataIsExpr = TRUE,powerVector = powers,corFnc = cor,corOptions = list(use = 'p'),networkType = "unsigned")
​## Power SFT.R.sq slope truncated.R.sq mean.k. median.k. max.k.
## 1 1 0.719 -1.700 0.874 40.60 37.900 102.0
## 2 2 0.521 -0.707 0.679 15.00 12.500 40.0
## 3 3 0.814 -0.476 0.764 9.92 7.970 25.9
## 4 4 0.900 -0.671 0.887 7.73 5.790 23.6
## 5 5 0.803 -0.809 0.748 6.47 4.140 22.2
## 6 6 0.749 -0.901 0.677 5.63 3.610 21.1
## 7 7 0.880 -0.913 0.846 5.02 3.100 20.2
## 8 8 0.885 -0.928 0.853 4.55 2.610 19.4
## 9 9 0.849 -0.940 0.806 4.17 2.170 18.6
## 10 10 0.918 -0.940 0.896 3.86 1.890 18.0
## 11 12 0.897 -0.942 0.867 3.36 1.610 16.8
## 12 14 0.882 -0.949 0.849 2.99 1.360 15.8
## 13 16 0.819 -0.996 0.770 2.69 1.180 15.0
## 14 18 0.890 -0.974 0.858 2.44 0.997 14.3
​## 15 20 0.885 -0.987 0.852 2.24 0.802 13.7
# Plot the results 
sizeGrWindow(9, 5)
par(mfrow = c(1,2));
cex1 = 0.9; 


# Scale-free topology fit index as a function of the soft-thresholding power
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");

# Red line corresponds to using an R^2 cut-off 
abline(h=0.80,col="red") 

# Mean connectivity as a function of the soft-thresholding power
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")
wgcna R • 2.7k views
ADD COMMENTlink modified 2.4 years ago by hygine0 • written 4.6 years ago by madkitty590
0
gravatar for hygine
2.4 years ago by
hygine0
Beijing
hygine0 wrote:

abline(h=0.90,col="red")

you can chose power=4.

ADD COMMENTlink written 2.4 years ago by hygine0
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 935 users visited in the last hour