[BioC] Analysing RNA-seq data

[Yinglei Lai]

Based on my experience, after a certain transformation, e.g. log(x+0.5), (+0.5 to avoid log(0) for the count x) either SAM or limma will perform well.  I think the permutation method is necessary for p-value evaluation.

Best,
Yinglei


----- Original Message -----
From: Gordon K Smyth <smyth at wehi.EDU.AU>
Date: Thursday, February 12, 2009 5:31 pm
Subject: [BioC]  Analysing RNA-seq data
To: Ingunn Berget <ingunn.berget at umb.no>
Cc: Bioconductor mailing list <bioconductor at stat.math.ethz.ch>


> Dear Ingunn,
> 
> Once the data has been summarized as counts for transcripts, the edgeR 
> 
> package will do a good job of differential expression between 
> conditions, 
> assuming there are some replicates.
> 
> Best wishes
> Gordon
> 
> > Date: Thu, 12 Feb 2009 10:18:17 +0100
> > From: Ingunn Berget <ingunn.berget at umb.no>
> > Subject: [BioC] Analysing RNA-seq data
> > To: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
> >
> > Are there any packages in Bioconductor for analysing RNA-seq data?
> >
> >
> > Ingunn Berget (Dr. Scient)
> > UMB, box 5003, IHA
> > 1432 ?s
> > Norway
> >
> > Centre for Integrative Genetics, www.cigene.no
> > Centre for Biospectroscopy and Data Modelling, www.specmod.org
> 
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