[BioC] EdgeR and libsize normalization

[Mark Robinson]

Hi Francois,

I'm a little confused as to what you are asking.

You asked a similar question last week:
https://stat.ethz.ch/pipermail/bioconductor/2012-July/047057.html


> Correct me if I am wrong but to have the counts after TMM I am doing :
> TMM_counts = raw_counts / ( libsize * norm.factor )

These are normalized "values", but they are, of course, no longer counts.  You could multiply by 1e6 and have a (normalized) counts per million interpretation.


> But how to get the counts after TMM and lib.size normalization ?

The edgeR user's guide says:

"The edgeR methodology needs to work with the original digital expression counts, so these should not be transformed in any way by users prior to analysis."

And, in your own words:

"[TMM] gives a normalization factor that will correspond to an offset in
the model that will test for differential expressed genes."

So, what do you actually mean be "counts after […] normalization"?  The normalization doesn't actually change the raw counts; it changes the offset in the model.


> Calling equalizedLibSizes(d) give me a common libsize (N value)
> But I am not sure how to rescale the normalise factor obtain on the raw counts.

equalizeLibSizes() gets used only for the purpose of estimating the dispersion parameter, and generally does not need to be called directly.  Do you have a reason for calling it directly?

Best,
Mark



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On 24.07.2012, at 10:58, François RICHARD wrote:

> Dear all,
> I am using EdgeR on RNA-seq data for differential analysis.
> 
> I would like to see the impact of the double normalizations (TMM +
> libsize) on the counts.
> 
> Correct me if I am wrong but to have the counts after TMM I am doing :
> TMM_counts = raw_counts / ( libsize * norm.factor )
> 
> But how to get the counts after TMM and lib.size normalization ?
> Calling equalizedLibSizes(d) give me a common libsize (N value)
> But I am not sure how to rescale the normalise factor obtain on the raw counts.
> 
> Can someone help me?
> 
> Thanks a lot
> 
> François
> 
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