DESeq2 counts as input for WGCNA
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Peny • 0
Last seen 11 days ago


Apologies in advance for the question-I am trying to make sense of RNA Seq and the stats behind it.

I am looking to use the transformed counts from DESeq2 as input to WGCNA. Since we are using a design when we create the DESeqDataSetFromMatrix before we get the counts (and depending on the factor/ combination of factors we use the counts slightly change), I was wondering if this would affect how WGCNA will correlate the modules with different traits (that might not be in the initial design).

An example:

I am trying to get transformed data counts using ~time_to_rebound (continuous variable, cut in 3 bins). In WGCNA I would like to see what modules correlate with age, time to rebound (as a continuous variable) and groupings of patients based on time to rebound but in different cut-offs.

Don't know if I making sense here but any help/ advice would be much appreciated!!

Thank you!!


WGCNA DESeq2 • 117 views
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Last seen 2 days ago
United States

Dear Penny,

From the DESeq2 side, the scaled counts (counts(dds, normalized=TRUE)) depend on the size factors. These depend on the samples included in the dataset but not on the design.

Entering edit mode

Thank you Michael!

Just an update to this, I read the WGCNA FAQ a bot more carefully now and their advice is to use the DESeq2 vst transformation. So, the whole process would be to:

  1. create the DESeqDataSetFromMatrix ( I am using a continuous variable cut in bins in the design, controlled by Sex and Country)
  2. filter for low counts (>=10 in 90% of all samples)
  3. vst
  4. removeBatchEffect for Sex and Country

Would this bias my WGCNA if I want to look at the continuous variable as a clinical trait?

Thank you again!!



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