Module preservation analysis using WGCNA

Module preservation analysis using WGCNA

0

Dear Friends,

I have the gene expression microarray dataset (about 17000 genes) of about 400 cancer samples with different cancer subtypes (say A, B, C, and D) and about 30 control samples. Here, I used only cancer samples and considered 50% of genes with the highest variance as input for WGCNA and selected signed network type. I considered subtypes as traits (binary traits) and used WGCNA to find the possible modules associated with traits and corresponding hub genes. I found that some modules are significantly associated with just subtypes A and B. In the next step, I applied module preservation analysis to examine if the associated modules with subtype A are preserved or non-preserved in other subtypes. So, I considered subtype A as a reference and other subtypes as a test and conducted the preservation analysis for each subtype and the reference, separately. As almost expected, associated modules with subtype A are non-preserved in other subtypes. However, I have some questions in this regard; kindly share with me your suggestions.

  1. Are the above working steps logical in your view? I’m also thinking of doing module preservation analysis with control samples as a reference and each subtype. But, I’m not still sure about it since the sample size of the control is almost small (28 samples) and some modules will be obviously non-preserved between control and each cancer subtype. Please kindly advise me with your helpful comments and suggestion.
  1. Regarding the module preservation analysis, as I read, the Zsummary parameter has a strong dependence on module size, so I used medianRank parameter and considered modules with medianRank ≥ 8 as non-preserved modules, is it acceptable?

Thanks in advance


cancer


expression


WGCNA


samples


gene

• 20 views

50 minutes ago by


seta

★

1.5k

Read more here: Source link