[BioC] RSEM for transcript and gene level read count and edgeR differential expression analysis

[Steve Lianoglou]

Hi,

On Mon, Aug 19, 2013 at 11:17 AM, Alan Smith <alan.sm310 at gmail.com> wrote:
> Hello,
>
> I used RSEM to extract gene and transcript level read count information for
> our single end read libraries. Then rounded off the expected read counts to
> use for differential expression analysis using edgeR at both transcript and
> gene level. However, I found that the number of DE transcripts were almost
> 10 times less than those of genes.
>
>  Is this expected or should I be following other package to analyze
> transcript level DE analysis.

If you take a minute to take a walk down memory lane and browse
through the list archives searching for "RSEM":

http://search.gmane.org/?query=rsem&author=&group=gmane.science.biology.informatics.conductor&sort=date&DEFAULTOP=and&xP=Zrsem&xFILTERS=Gscience.biology.informatics.conductor---A/

You'll find that RSEM output doesn't play well with edgeR and DESeq.
These methods explicitly require *count* data -- not any old number
that has been then rounded to an integer.

I recall a thread about how voom would likely work well with RSEM
output, but I can't seem to dig it up right now -- I'm only finding
other people mentioning that thread ;-)

HTH,
-steve

-- 
Steve Lianoglou
Computational Biologist
Bioinformatics and Computational Biology
Genentech