hi Richard,


On Mon, May 13, 2013 at 11:06 AM, Hickman, R.J. (Richard) <R.J.Hickman@uu.nl
> wrote:

> Dear All,
>
> I am looking for some feedback regarding the use of the
> variance-stabilization (VST) methods found in the DESeq2 package. For me,
> the purpose for applying this transformation is to be able to generate
> moderated fold changes for clustering of genes (not samples as described in
> the DESeq vignette).


> My data consists of a time series, where for each time point there is a
> "treated" sample and a "control" sample. Each sample (timepoint) consists
> of 4 biological replicates.
>
> I performed the VST on the entire set of data


Could you share the code (and sessionInfo()) you used to create the object
which you applied the transformation to?  For example, in the vignette, in
order to perform unsupervised clustering, we estimate the dispersions in a
manner which is blind to the experimental design.

ddsBlind <- dds
design(ddsBlind) <- formula(~ 1)
ddsBlind <- estimateDispersions(ddsBlind)
vsd <- varianceStabilizingTransformation(ddsBlind)

I would guess you are observing variance across the timepoints. If you are
not using the "blind" method from the vignette, the design is used by
estimateDispersions() which might result in rows with smaller dispersion
estimates when the variance is due to different timepoints, but not
used by rowVars()
so you observe large row variance.

best,

Mike

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