Thanks Davis and Kasper for your reply.
So if I understand correctly, after I add the offset to the DGEList, I
continue with estimating common dispersion (so skipping the calcNormFactors
step).
And if so, would you suggest to do quantile normalization after adjusting
the read counts to gene length, and before estimating the common dispersion?
Mali

On Thu, Aug 4, 2011 at 2:40 AM, Kasper Daniel Hansen <
kasperdanielhansen@gmail.com> wrote:

> On Wed, Aug 3, 2011 at 7:09 PM, Davis McCarthy <dmccarthy@wehi.edu.au>
> wrote:
>
> > We have used this gene-specific normalization factor to try out things
> like quantile normalization on RNA-Seq data in house. To my knowledge, the
> new cqn package outputs gene-specific offsets that will plug in to edgeR to
> normalize data for (possibly among other things) gene length and GC bias.
>
> True, but the interface to the cqn normalization method assumes that
> the data is ordered in a "genes" by samples matrix and that all
> samples have the same length/gc content for a given gene.  The data we
> are discussing does not fit into this framework.  However, it might be
> possible to hack the function to deal with this, by running
>  cqn(..., sqn = FALSE)
> on each species separately, combining the output and then do a custom
> sqn normalization of the combined residuals.  Hmm, this clearly
> requires more than 60 secs. of thinking (and probably some careful
> looking at the output to get an idea of whether this gives useful
> output or makes things worse).
>
> Kasper
>

	[[alternative HTML version deleted]]

