WGCNA analysis on RNAseq and proteoimcs data
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sagigordon • 0
@sagigordon-23177
Last seen 18 months ago

Hi all, I'm trying to use WGCNA analysis on both proteomics and RNA-seq data. I succeed in getting some modules that are correlated to clinical traits, but most of the modules were not significant. Even these modules which were significant, when I have tried to enrich the modules to the trait, I haven't got a lot of processes. the bigger problem from me was in the RNA-seq. I have tried filtering of genes with some options and I wondering, which one is the best to get better results. scale-free topology got almost 0.9... from your experience, what should I use to filter genes (low variation/ filter 0 values?) should I change specific parameters in some functions to construct a better co-expression network? If you can share with me more tips, I'm will be glad to hear, I'm new in R and trying to improve my abilities and result Thanks a lot! Sagi

cancer • 177 views
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@peter-langfelder-4469
Last seen 12 months ago
United States

You may want to read WGCNA FAQ. Filtering might help but I would not expect miracles.

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