Question: WGCNA Network Analysis
gravatar for skjobs0123
11 months ago by
skjobs012340 wrote:

I'm trying to use WGCNA for weighted network analysis. I'm getting trouble how to decide this parameter. It's clear how to define and why this has been defined.

#Choosing a soft-threshold to fit a scale-free topology to the network

powers = c(c(1:10), seq(from = 12, to=20, by=2));

What is the meaning of this powers and how to decide this value?

wgcna R • 605 views
ADD COMMENTlink modified 11 months ago by Renesh1.7k • written 11 months ago by skjobs012340

I suggest to first get an overview of the method, for example with this lecture from the WGCNA developer, which also covers the power parameter.

ADD REPLYlink written 11 months ago by ATpoint25k
gravatar for Jean-Karim Heriche
11 months ago by
EMBL Heidelberg, Germany
Jean-Karim Heriche21k wrote:

This parameter must be >1 and is simply the power to which the correlations are raised. This increases the contrast between high and low values, in effect a form of soft thresholding. In the paper, the authors suggest setting it so that the resulting network has a scale-free topology. See the pickSoftThreshold() function in the WGCNA R package.

ADD COMMENTlink written 11 months ago by Jean-Karim Heriche21k
gravatar for Renesh
11 months ago by
United States
Renesh1.7k wrote:

In WGCNA, power parameter is needed to reduce the spurious correlations in the data. To select a power from pickSoftThreshold function, choose reasonably high R^2 (column 2), usually higher than say .85 and negative slope around -1 (column 4) to get an approximately scale-free network. Power is helpful to easily differentiate strong and weak correlations.

ADD COMMENTlink written 11 months ago by Renesh1.7k
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