[BioC] edgeR: Using ratios (translational efficiencies) as input

[Gordon K Smyth]

Dear Gowthaman,

I'm not quite sure what translational efficiencies are.  Do you have a 
different efficiency value for each gene and each RNA sample?  If you do, 
why not take logs of the ratios (offsetting counts by 1/2 or 1 to avoid 
zeros) and feed them into limma?

Best wishes
Gordon

> Date: Fri, 26 Apr 2013 15:22:28 -0700
> From: gowtham <ragowthaman at gmail.com>
> To: bioconductor <Bioconductor at r-project.org>
> Subject: [BioC] edgeR: Using ratios (translational efficiencies) as
> 	input
>
> Hi Everyone,
> I have been using edgeR for the last couple years with great success.
> Thanks very much. Now I have slightly unconventional dataset to try. We
> have two groups to compare (life stages) each with three replicates. But,
> for each sample in each group, we made two different RNAseq libraries.
> 1)   one from fragmented mRNA (classical RNAseq) and
> 2)  another from Ribosome-bound RNA fragments. This library would indicate
> how much of the RNA is actively being translated.
>
> I have used edgeR to analyse data from each of this separately (data from
> classical RNAseq or Ribosome-bound). So this let us study the
> differentially transcribed genes or differentially translated genes.  And
> got really nice results.
>
> The next step is to compare the translational efficiencies between them. In
> each sample the ratio between read counts of Ribosome bound mRNAs and
> fragmented mRNA would give us the translational efficience of that gene. We
> can generate these efficiences (ratios) for each of the three replicates in
> each group. Can I feed this data to edgeR to find out which genes have
> 'differential efficiencies'  between groups?
>
> I understand, edgeR insists on NOT normalizing the read counts and all the
> further statistics depends on the total library size count. By, using
> ratios, i completely throw edgeR off. But, i am not sure what is the best
> alternate to this?
>
> Any ideas?
>
> Much thanks in advance,
> Gowthaman
>
>
> -- 
> Gowthaman
>
> Bioinformatics Systems Programmer.
> SBRI, 307 West lake Ave N Suite 500
> Seattle, WA. 98109-5219
> Phone : LAB 206-256-7188 (direct).
>

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