yuan.x.hao at gmail.com
Fri Sep 5 17:17:33 CEST 2014
You obviously allowed multiple mappings when calling STAR, however, HTSeq counts only uniquely mapped reads. ~1.5M reads mapped to intergenic and/or intronic regions which contributed to _no_feature. _ambiguous mapped to regions annotated by multiple genes.
If you want to take into account multiple mapped reads, you can either evenly distribute them to all gene targets (normalized by times of mapping), distribute them according to uniquely mapped reads, or distribute them more sophistically by doing a multiple-run EM algorithm (such as the RSEM does).
On Sep 5, 2014, at 10:41 AM, Julia [guest] <guest at bioconductor.org> wrote:
> Hi all,
> I am new to the field of seq and performed a RIP-Seq experiment using HTSeq count as counter.
> I get now the following (using union, but doesnÂ´t look better for interesection_strict):
> __no_feature 1503377
> __ambiguous 490772
> __too_low_aQual 0
> __not_aligned 0
> __alignment_not_unique 5277314
> When I sum up counts for all genes, I get 3227845.
> The number for __no_feature, __ambiguous, __alignment_not_unique look very high.
> Does somebody have an idea for that?
> (Additional info: We did random priming and mapped with STAR and masked rRNA loci)
> Best wishes
> -- output of sessionInfo():
> Sent via the guest posting facility at bioconductor.org.
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