[BioC] edgeR:Differences in results between two different versions of edgeR

Dorota Herman dorota.herman at psb.vib-ugent.be
Mon Dec 3 19:36:58 CET 2012


Dear list,

when I run the same code for RNA-seq data to find differentially 
expressed genes using exactTest() in two different versions of edgeR, I 
obtain considerable different results. The data set contains 36 
libraries divided into 12 groups, where each library is consist of 24 
000 genes (none of them has all zero counts). While the older version 
(edgeR_2.0.5) gives me 97 significantly differentially expressed genes 
between two selected groups, the newer version (edgeR_3.0.4) does not 
find any significantly differentially expressed genes; moreover FDR is 
less than 1 only for 13 genes. I realize these two versions are far from 
each other in their developmental process. However, I would be still 
interested in reasons of such a difference.

Running in parallel the same code in two different versions of edgeR, I 
find out that it is most likely attributed by the estimateTagwiseDisp() 
function, which are

estimateTagwiseDisp(object, prior.n=10, trend=FALSE, prop.used=NULL, 
tol=1e-06, grid=TRUE, grid.length=200, verbose=TRUE) in edgeR_2.0.5

and

estimateTagwiseDisp(object, prior.df=20, trend="movingave", span=NULL, 
method="grid", grid.length=11, grid.range=c(-6,6), tol=1e-06, 
verbose=FALSE) in edgeR_3.0.4

The greatest impact seems to have parameters prior.n prior.df as their 
settings say how much we want our tagwise dispersion be influenced by a 
common dispersion. Although setting a prior.df to very low (that would 
be an equivalent of a high prior.n) makes a difference in FDR values, 
the results from two different edgeR versions are still very distinct, 
so are estimated $tagwise.disperion parameters . Another candidate 
parameter for changes seems to be the prop.used but I am not sure if its 
equivalent in edgeR_3.0.4 is “span” parameter, is it? On the other hand 
there are parameters related to the estimation algorithm, that I would 
not expect to cause such a difference in the further outcome, could they?

What am I missing here? Settings of which parameter would make outcomes 
of DE genes analyses more comparable between two different edgeR versions?

Best wishes
Dorota


-- 
==================================================================
Dorota Herman, PhD 
VIB Department of Plant Systems Biology, Ghent University
Technologiepark 927
9052 Gent, Belgium
Tel: +32 (0)9 3313692
Email:dorota.herman at psb.vib-ugent.be
Web: http://www.psb.ugent.be



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