[BioC] edgeR v2.6 vs. v3.2.4

[mwheeler [guest]]

Hi, 

I have been working with edgeR to find differentially expressed genes for RNA-seq data. I have been working with a data set with 3 treatment groups and a total of 10 samples per treatment group. The samples were sequenced as single-end, stranded reads. I first analyzed this dataset with the edgeR v2.6 and was getting 100-300 ( FDR<0.05, tagwise dispersion with prior.n=20) differentially expressed genes for each pairwise comparison. I upgraded to version 3.2.4 this weekend and reanalyzed the same dataset. I now get <100 genes as being differentially expressed (FDR<0.05, tagwise dispersion with prior.df=20) across comparisons. Does anyone know why there would be such a big difference in # of genes being called DEGS? The smaller gene list is complete subset of the larger gene list so I am assuming that some upgrades caused edgeR to be more conservative. 

Thanks,
Marsha

 -- output of sessionInfo(): 

R version 3.0.1 (2013-05-16)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] edgeR_3.2.4  limma_3.16.7


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