Dear list,
Apologies for posting this to both Bioconductor and here. I recently read a
Bioconductor post where the
developer of the WGCNA suggested the use of the package for RNA-seq data
analysis after implementing a variance stabilization normalization to
the raw counts. I have read the tutorials and run the example dataset at
http://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/index.html.
I would like to apply WGCNA to my RNA-seq data consisting of 1000
transcripts whose expression is measured for 50 triplicated cell types
(approximately 150 samples) and derive networks.
I would
like to ask if WGCNA can be used successfully in this kind of
heterogeneous dataset where, for most of the transcripts, the various
cell types expression patterns might differ substantially (so that a
variance stabilizing transformation will not give me approximately
normal distribution for each transcript; it would rather be a mixture of
normal distributions).
Thank you,
Pan
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