Question: What data should i use to generate a gene coexpression network?
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gravatar for tahermun
3.8 years ago by
tahermun0
United States
tahermun0 wrote:

I have a microarray dataset that contains expression data of 30 samples of individuals with a certain disease and 30 samples of healthy individuals. After restricting this data to the most significantly differentially expressed genes, I want to use the WCGNA R package to perform a gene coexpression network analysis. Ideally, I want to look at the coexpression network of the disease data and the coexpression network of the healthy data separately, so I was thinking about separating the data and running WGCNA separately on both types of samples. Would this give me bad results? Do I need multiple types of samples to construct a correlation network?

Essentially, my  question is: do I need different classes of samples to perform one coexpression network analysis, or could I construct a network for each class separately?
 

microarray co-expression R • 1.9k views
ADD COMMENTlink modified 3.8 years ago by Deepak Tanwar3.9k • written 3.8 years ago by tahermun0
2
gravatar for Deepak Tanwar
3.8 years ago by
Deepak Tanwar3.9k
ETH Zürich, Switzerland
Deepak Tanwar3.9k wrote:

 I was thinking about separating the data and running WGCNA separately on both types of samples. Would this give me bad results?

I don't think so.

 

 

question is: do I need different classes of samples to perform one coexpression network analysis, or could I construct a network for each class separately?

In principle, you should construct the coexpression networks separately. Then only you would be able to compare the gene networks. 

ADD COMMENTlink written 3.8 years ago by Deepak Tanwar3.9k
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