[BioC] DESeq on transcripts v/s genes

[Wolfgang Huber]

Dear Abishek

there was some anxiety regarding double-counting / redundancy in this 
thread. Actually, there is very little reason to worry. DESeq tests 
sequentially one hypothesis after the other. It does not matter whether 
they are correlated or not.

The one consideration where the correlations / redundancy can matter is 
multiple testing correction. As long as you go for FDR, again there is 
little to worry, since the redundancy pops up both in the numerator and 
denominator of the ratio (the "R" in FDR) and at least to good enough 
approximation cancels out.

If you go for family-wise error rate (FWER) and, say, Bonferroni 
correction, then the redundancy and the increase in number of tests do 
matter. But there seem few reasons to use FWER/Bonferroni in this context.

	Hope this helps
	Wolfgang

Feb/2/12 12:46 AM, Abhishek Pratap scripsit::
> Hi All
>
> I am wondering if conceptually I can use the DESeq to test for differential
> transcript expression compared to genes. In our case we have generated a
> transcript model based on RNA-Seq and if we try to collapse those
> transcripts to genes in order to do gene level differential expression many
> exons are collapsed to give rise to artificial exons.
>
>
> eg :
>
>
> Transcript 1 :        ---------------------- (exon)
> Transcript 2 :                        -----------------------------(exon )
>
> Gene level :          -------------------------------------------- (exon)
>
> Also another thing that comes to my mind if the effect of double counting
> if I take the read counts at transcript level due to exon redundancy.
>
> I would love to hear from your experience.
>
> Thanks!
> -Abhi
>
> 	[[alternative HTML version deleted]]
>

Best wishes
	Wolfgang

Wolfgang Huber
EMBL
http://www.embl.de/research/units/genome_biology/huber