Is VST-normalization (a la DESeq) considered the right way to deal with
large scale differences in mean "baseline" expression across experimental
blocks?  Is there a normalization method that can take into account the
design matrix (or at least the batch/block columns)?  I don't want to
remove the batch/block effects, but TMM and friends all assume
near-constant expression across the design, which is violated by our
(nuisance) block-level differences in composition.  We see this when we
compare edgeR TMM-normalized log(cpm) to qRT-PCR data; the
TMM-normalization has smoothed out the block differences that the Ct values
still exhibit (though cpm and Ct are still strongly correlated, there is a
Ct "shift" for each different block that is not seen in the cpm).

Thanks in advance for any insights/thoughts on the issue,
-Aaron

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