[BioC] Can we apply WGCNA to RNA-seq dataset?

Peter Langfelder peter.langfelder at gmail.com
Fri Mar 7 08:45:38 CET 2014

Hi Spanos,

you can certainly use WGCNA for RNA-seq data. Two recommendations: 1.
Filter out genes whose count is less than say 5 in more than say 80%
of the samples. This gets rid of a lot of noise and gets rid of
expression profiles for which correlation makes little sense. 2. Use a
variance-stabilizing transformation, such as the one implemented in
varianceStabilizingTransformation or rlogTransformation in the DESeq2.

I have analyzed a few RNA-seq data sets and have had great results.

Hope this helps,


On Thu, Mar 6, 2014 at 4:32 PM, spano spano <diadiktuo at outlook.com> wrote:
> Hi Faranak,
> Did it work for you the WGCNA with the normalized values? Did you  find another possible solution?
> When I use the normalized values it gives me a weird scale free topology model fit.
> Thank you,
> Spanos
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