I cannot tell whether you have done something wrong without more
of your analysis.
Presumably you used the GLM approach and the likelihood ratio test for
identifying DE genes, and if you followed the users guide then the
results should be correct.
I think it is just because those samples are not very different from
each other, which is possible for some RNA-Seq data sets.
One way to look at the difference between those samples visually is to
plot the Smear plots (see case studies in the users guide), and see
whether you have a lot of genes with large logFC.
> Message: 1
> Date: Mon, 13 Aug 2012 13:54:09 +0300
> From: KJ Lim<jinkeanlim at="" gmail.com="">
> To: Bioconductor mailing list<bioconductor at="" r-project.org="">
> Subject: [BioC] edgeR: DE summary of decideTestsDGE
> <cadu1pczupg6g24-27m_h3h-cwelfw415emjhk+-hqwjgxaxiyq at="" mail.gmail.com="">
> Content-Type: text/plain; charset=UTF-8
> Dear edgeR and R community,
> Good day.
> I'm using the edgeR to analysis my RNA-Seq data which contained 2
> genotype (HS,LS) and different time points (0H, 3H, 24H, 96H). The
> differential analysis was carried out based on the guide of the
> edgeR user's guide (Chapter 3, section 3.3).
> May I ask it that common to obtain the summary of differentially
> express (DE) genes like below? The number of DE genes seemed very
> little in my case, HS vs LS at 24H
> > summary(dt.hvsl24h<- decideTestsDGE(lrt.hvsl24h,
> adjust.method="BH", p.value=0.05))
> -1 3
> 0 46997
> 1 4
> The summary of DE genes was none when I carried out the
> for the HS vs LS at 96H. May I ask is that common or I have done
> something wrong in between?
> Thank you very much for your time and advice.
> Have a nice day.
> Best regards,
> KJ Lim
Walter and Eliza Hall Institute of Medical Research,
1G Royal Parade, Parkville, Vic 3052, Australia.
yuchen at wehi.edu.au
The information in this email is confidential and