[BioC] DESeq2 - regularised log transformation blind or not?

[Mike Stubbington]

Hi,

I have just been reading the updated vignette for DESeq2 in the bioconductor devel branch (http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.pdf) and was interested by the comments in section 2.1.1 about the appropriateness of setting the blind argument when performing regularised log transformation. Specifically, the comment that

“...blind dispersion estimation is not the appropriate choice if one expects that many or the majority of genes (rows) will have large differences in counts which are explanable by the experimental design…”

Given this, I would really appreciate some further advice about when one should set blind=FALSE.

For example, I am performing gene clustering using RNA-seq data for different six cell types. I would certainly expect a lot of genes to vary between the samples. Is this a case when blind=FALSE might be appropriate? 

Thank you for your help,

Mike