This is in regards to a previous post by Dr. Gordon Smyth from June, 2012.
https://stat.ethz.ch/pipermail/bioconductor/2012-June/045950.html

In the previous post, Dr. Smyth stated:
"voom() isn't currently setup to accept the normalization matrix from cqn,
but it will be down the track."

Does anyone know whether voom() can now accept CQN normalized output? I was not able to find anything in the limma user documentation on whether voom can now handle CQN normalized data as input. I'm trying to correct for sample-specific variability prior to running voom normalization and limma differential expression. I have been reading publications on sample-specific technical variability (e.g. Risso, et al.  BMC Bioinformatics 2011). Is it still recommended to do within-lane quantile normalization prior to differential expression? My data is RNA-Seq from Illumina HiSeq using standard Illumina processing. I definitely have the random hexamer priming issue, but that should (theoretically at least) be consistent across samples for a single gene as Dr. Smyth points out in the previously referenced post.

Any insight would be great.

Kind regards,
Heather



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