[BioC] Counting reads for edgeR or voom()

[Wei Shi]

Hi Davide,

>From my point of view, counting reads overlapping exons is easier than counting reads overlapping with transcripts because exons are much better characterized than transcripts. The exon annotation is easy to obtain, for example the RefSeq annotation (or annotations from Bioc packages). Another problem with summarizing reads to transcripts is that transcripts are more likely to overlap with each other compared to exons, which leads to the issue of which transcript a read should be assigned to if it falls within the common region. This is an issue for summarizing reads to exons as well, but it is not as serious as that for transcripts.

Hope this helps.

Cheers,
Wei



On Jul 3, 2012, at 10:06 PM, Cittaro Davide wrote:

> Hi all, just a quick question on best practices to create datasets for RNA-seq analysis with edgeR or limma:::voom().
> I must create a table in which read counts for every entity (i.e. every transcript) for every sample. In order to do this I have at least a couple of options that may affect results:
> 1- should I count all reads overlapping the whole transcript or the reads that overlap exons?
> 2- should I use every transcript or just the primary one?
> 
> Thanks
> 
> d
> 
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