[BioC] DESeq nbinomGLMTest specific comparisons

Ryan C. Thompson rct at thompsonclan.org
Fri Jan 10 18:18:43 CET 2014

In general, you would subset the CountDataSet to only include the 
samples from the two conditions you care about. Do this after 
estimating dispersions and before fitNbinomGLMs.

But more generally, I agree that the real solution is "use DESeq2".


On Thu 09 Jan 2014 03:41:39 AM PST, James Floyd wrote:
> Hi,
> Thanks for your reply, and sorry for the delay. As always, I got
> distracted by other projects Š
> I am looking to perform a DE analysis for a disease with three states,
> while correcting for smoking status. So I was using Š :
> fit0 = fitNbinomGLMs( cdsFull, count ~ smoking )
> fit1 = fitNbinomGLMs( cdsFull, count ~ smoking + condition )
> Š then comparing the models to see whether adding condition improves the
> fit of the model and has a significant effect (as described in the
> vignette).
> However, if I wanted to make a specific comparison of, say, the two most
> extreme disease states (state A against C, ignoring B), how would I go
> about doing this?
> Thanks for letting me know about DESeq2, I was unaware of it.
> Cheers,
> Jamie
> On 27/11/2013 17:21, "Steve Lianoglou" <lianoglou.steve at gene.com> wrote:
>> Hi,
>> On Tue, Nov 26, 2013 at 8:21 AM, James Floyd <j.a.floyd at qmul.ac.uk> wrote:
>>> Hi,
>>> I notice in the DESeq
>>> vignette<http://bioconductor.org/packages/release/bioc/vignettes/DESeq/in
>>> st/doc/DESeq.pdf> there is a "Fixme" comment about including how to test
>>> specific comparisons using nbinomGLMTest (page 12). It would be great if
>>> someone with experience doing this could let me know how it is done.
>> Can you be more specific of what you'd like to test? Perhaps you can
>> setup your problem for us and point out what particular comparison
>> you'd like to make, and someone can help you better.
>> Furthermore, if you are using DESeq, you might consider shifting over
>> to DESeq2. It offers a number of benefits over DESeq, and (I believe)
>> this is where the DESeq authors are focussing the lion's share of
>> their attention anyhow.
>> -steve
>> --
>> Steve Lianoglou
>> Computational Biologist
>> Genentech
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