[BioC] DESeq and transcript-wise analysis

[Thomas Girke]

This study contains some strand specific RNA-Seq data:
http://www.hubmed.org/display.cgi?uids=18423832

I would expect that most RNA-Seq experiments in the near future may be
performed in a strand-specific manner, since the strand information
carries a lot of biologically relevant information in this application
domain. Thus, adding analysis support for it is definitely not a waste
of time.

I have not used easyRNASeq yet, but I will certainly give it a try.

In my group we currently use for RNA-Seq analysis the following
components: Rsubread (or tophat) -> rtracklayer/Rsamtools/GenomicRanges
-> DESeq/edgeR. This allows any type strand and non-strand specific read
counts for exons, transcripts, genes, intergenic features, etc. A huge
advantage of this environment is its flexibility and broad application
spectrum for most applications domains in the NGS field, such as
SNP-Seq, ChiP-Seq, smallRNA-Seq, etc. For instance, our ChIP-Seq
analysis routines use most of these tools plus some peak callers.

Thomas

On Thu, Feb 09, 2012 at 01:38:02PM +0000, Nicolas Delhomme wrote:
> Dear Abhi,
> 
> If you could point me to some published strand specific data or let me get an excerpt of yours, I could easily had strand-specificity in the easyRNASeq package.
> 
> Thanks,
> 
> Nico
> 
> ---------------------------------------------------------------
> Nicolas Delhomme
> 
> Genome Biology Computational Support
> 
> European Molecular Biology Laboratory
> 
> Tel: +49 6221 387 8310
> Email: nicolas.delhomme at embl.de
> Meyerhofstrasse 1 - Postfach 10.2209
> 69102 Heidelberg, Germany
> ---------------------------------------------------------------
> 
> 
> 
> 
> 
> On 9 Feb 2012, at 00:41, Abhishek Pratap wrote:
> 
> > Hi Elena
> > 
> > Good timing with me on this. I recently was contemplating the best way
> > to move forward for a similar analysis. HTSeq  a python based toolkit
> > by Simon can help you do the counting.  FYI : It can also take strand
> > info into account.  If you dont have stranded data you could also look
> > at easyrnaseq package.
> > 
> > So if you have an annotation file like gff/gtf with the isoform
> > information you could then do the read counting at isoform or gene
> > level based on which attribute of the gff file you select to do the
> > counting. Check out
> > http://www-huber.embl.de/users/anders/HTSeq/doc/count.html.
> > 
> > Also you want to keep in mind that at isoform level you would be
> > double counting the reads in exons which are shared in the isoforms
> > which can bias your results to some extent. But as Wolfgang pointed
> > out in a recent post if you use FDR, it should not matter a lost as
> > the bias will be cancelled between denominator /numerator.
> > 
> > You also might want to check the DEXSeq which can help infer
> > differential expression from RNA-Seq exons which could then be related
> > back to genes/isoforms.
> > 
> > Hope this helps and let us know about your progress. I would be
> > interested in learning from your experience too.
> > 
> > Cheers!
> > -Abhi
> > 
> > ----------------------------------
> > Abhishek Pratap
> > Bioinformatics Systems Analyst - 3
> > DOE- Joint Genome Institute
> > Lawrence Berkeley National Lab
> > 
> > 
> > 
> > 
> > On Wed, Feb 8, 2012 at 3:26 PM, Elena Sorokin <sorokin at wisc.edu> wrote:
> >> Greetings all,
> >> 
> >> After re-reading related posts in the listserv archive, I still didn't know
> >> the exact answer to my question, so here goes. I'd like to use DESeq to
> >> measure differential isoform expression. Has Simon or anybody else written a
> >> script that will convert aligned reads (.bam/.sam file) into a table of
> >> isoform counts, suitable for input to DESEq - similar to what Simon has done
> >> at the gene-wise level, but instead for making a table of counts by isoform?
> >> 
> >> I would try to do this myself, but I'm a novice at programming. Sorry if
> >> this has been answered elsewhere... If so, please let me know the link.
> >> 
> >> Thanks,
> >> Elena
> >> 
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