[BioC] EdgeR condition-specific dispersion

Robert Castelo robert.castelo at upf.edu
Mon Oct 8 09:44:06 CEST 2012

Dear Thomas,

if you have 10 or more samples per condition you could try the tweeDEseq 
package which is based on a more flexible family of count data 
distributions, the Poisson-Tweedie, and will estimate different 
dispersions and shapes per condition. the shape is a third parameter 
which provides additional flexibility over the negative-binomial to fit 
distributions with features such as heavy-tails or zero-inflation.


On 10/02/2012 07:15 PM, Thomas Frederick Willems wrote:
> I'm dealing with a factorial RNA-seq data set in which cells have  been stimulated with various combinations of extra-cellular cues. As 
such, I was interested in applying the GLM framework in edgeR to assess 
the contribution of each extra-cellular cue to the differential 
expression of certain genes. My concern, however, is that both the 
expression level and the dispersion of each gene varies greatly with the 
combination of cues. EdgeR doesn't seem to estimate condition-specific 
dispersion but rather one dispersion per gene (if the tagwise options is 
used). My question is therefore two-fold:
> 1) Does it make sense to want to estimate condition-specific dispersions?
> 2) Is there a way to modify the edgeR framework so that it does this?
> Thanks
> Thomas
> 	[[alternative HTML version deleted]]
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Robert Castelo, PhD
Associate Professor
Dept. of Experimental and Health Sciences
Universitat Pompeu Fabra (UPF)
Barcelona Biomedical Research Park (PRBB)
Dr Aiguader 88
E-08003 Barcelona, Spain
telf: +34.933.160.514
fax: +34.933.160.550

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