WGCNA Co-expression network analysis on cuffdiff output
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sbbinfo90 • 0
@sbbinfo90-17078
Last seen 5.6 years ago

Hello,

I am struggling with running WGCNA on cuffdiff output consisting of 28 pairwise comparisons (Time series Analysis). Can someone suggest way out to perform WGCNA for each comparisons separately?

Thanks!

WGCNA cuffdiff • 1.4k views
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How many samples do you have?

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It's not clear what your goal (research question you are trying to answer) is. For most data sets that I normally come across you would not run 28 different WGCNA analyses (unless you have 1000+ samples); you would run one or perhaps a few different WGCNA analyses and then relate modules to pairwise time point comparisons/contrasts. If you have the time series and you want to compare module "expression" in 28 different time points vs. a baseline (or pairwise time point comparisons) you could binarize the time point indicator into 28 binary variables. You could simply do that with model.matrix, but WGCNA contains functions specifically tailored to this. You may want to read (self-promotion alert) this text for more details.
 

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Hello Peter,

I have 8 samples (1 control and 7 infection stages) and my objective is to study genes co-expression amongst all pairwise comparisons. I already have Differentially expressed genes from Cuffdiff for all comparisons also. Can you please guide how to perform WGCNA on such data?  

There ate 3 replicates of each sample.

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Cross-posted on Biostars: https://www.biostars.org/p/338241/

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There's not much advice I can give you - just run a plain WGCNA analysis, and relate the resulting eigengenes to all the pairwise comparisons. If some infections have a very large effect, you may need to run several analyses, one with all infections, then possibly additional analyses with samples with some infections removed.

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