[BioC] Small RNA seq data analysis using DESeq

[Wolfgang Huber]

On Jun 19, 2013, at 8:44 pm, Vedran Franke <vfranke at bioinfo.hr> wrote:

> 
> Dear Simon,
> 
> I have a question regarding the analysis of small RNAseq data using DESeq.
> While counting the reads per loci I have weighted the reads by the
> reciprocal of the places to which the read maps.
> I was wondering whether it is still proper to use the negative binomial
> test implemented in DESeq (after rounding the expression estimates) to
> determine which loci are differentially expressed?
> 


Dear Vedran

DESeq is not intended to work with such values. However, the issue has nothing to do directly with the DESeq2 method or software, but a lot with the fact that it does not make scientific sense to ask from your data more than they contain.
- if you want to look for differential expression of loci, then you need measurements that probe these loci's expression in a specific way (e.g. unique mapping reads)
- if do not have such an specificity, then you need to aggregate your 'loci' into equivalence classes of things that are not distinguishable by your assay, until you have specificity.

	Hope this helps to proceed
	Best wishes
	Wolfgang

> Best regards,
> 
> Vedran Franke
> 
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