Hi Michael,

Yes, This what I wanted to known. Thank you.:)

Kind Regards


On Fri, Nov 1, 2013 at 2:02 PM, Michael Stadler <michael.stadler@fmi.ch>wrote:

> Hi Reema,
>
> If I understand your question correctly, I think the answer is: It depends.
>
> Counting alignments per exon may allow you to pick up differential
> splicing or differential isoform usage unrelated to splicing (e.g.
> alternative promoter usage or alternative termination).
>
> However, robust estimation of exon levels will require much greater
> sequencing depth; assuming that a gene has on average about ten exons,
> then you would need about ten times more reads to get a similar
> magnitude of counts. If you don't have that data or are not interested
> in within-gene structural differences, gene level estimates may be the
> better choice.
>
> Of course, you could try out both and compare results. You can easily
> get such counts from a bam file using countOverlaps (see workflow at
> http://www.bioconductor.org/help/workflows/high-throughput-sequencing/),
> or with the QuasR package, getting gene and exon counts is as simple as:
>
> gn <- qCount(proj, txdb, reportLevel="gene")
> ex <- qCount(proj, txdb, reportLevel="exon")
>
> Michael
>
>
>
> On 31.10.2013 21:19, Steve Lianoglou wrote:
> > Hi,
> >
> > On Thu, Oct 31, 2013 at 1:04 PM, Reema Singh <reema28sep@gmail.com>
> wrote:
> >> Hi Steve,
> >>
> >> Thank you for your reply,
> >>
> >> I just want to known what is the idea feature for summarizing read count
> >> after alignment?. Gene,transcript,exons features from GFF/GTF files are
> >> frequently used .
> >
> > If you are asking what the "ideal" format for storing summarized read
> > counts is, I would have to say that in "the R world" that would be to
> > use a SummarizedExperiment (it is a class defined in the GenomicRanges
> > package).
> >
> > The rowData() of the SummarizedExperiment would contain the GRanges
> > (or GRangesList) that define where the counts in each row of your
> > assay are from, and the columns would tell you the counts for a given
> > experiment.
> >
> > You could store your relevant sample data in `colData`, ie. phenotypic
> > data for each experiment (column), like cell type, perturbation,
> > whatever. See ?SummarizedExperiment for more info.
> >
> > If you were asking something else -- sorry, I'm still not getting what
> > the question is and perhaps someone else can chime in.
> >
> > -steve
> >
>
>


-- 
Reema Singh
PhD Scholar
Computational Biology and Bioinformatics
School of Computational and Integrative Sciences
Jawaharlal Nehru University
New Delhi-110067
INDIA

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