Differential testing after qsmooth normalization
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tycho-kirchner commented
Hi, and thank you for sharing this package.
Currently, I analyze multiple RNAseq datasets where a virus likely triggered a transcriptional shutdown, so global differences between samples are to be expected. I would like to kindly ask for recommendations/best practices on how to proceed with differential testing using e.g. limma/edgeR or Deseq2. Specifically, using limma-voom, currently I use a script similar to this but without calcNormFactors
on the already quantile normalized data. Similarly, with Deseq2 I set sizeFactors(dds) <- 1.0
before calling DESeq(dds,
. Would you consider this approach correct?
Thanks
Tycho