[BioC] normalization method & dispersion estimation RNA-seq data

[Gordon K Smyth]

Dear Anna,

> Date: Mon, 26 Nov 2012 09:30:19 -0800 (PST)
> From: "aec [guest]" <guest at bioconductor.org>
> To: bioconductor at r-project.org, aesteve at pcb.ub.es
> Subject: [BioC] normalization method & dispersion estimation RNA-seq
> 	data
>
> Is it possible to adopt the CQN normalization method (Hansen, 2012) as 
> an option of the edgeR function 'calcNormFactors' ?

No it isn't possible, because calcNormFactors() implements scale 
normalization methods, and cqn is not of this type.

But why do you need this anyway?  The cqn package has always worked with 
edgeR, and the cqn package provides code examples of how to do this.
What are you looking for that is not already provided?

> And the new shrinkage estimator for dispersion (Wu, 2012) that seems to 
> be better than the currently used by edgeR ?

It is inevitable that each new paper that is published claims to have to 
best method.  In our own (unpublished) simulations with the DSS package 
that goes with Wu et al (Biostatistics, 2012), we find that it is similar 
in performance to DESeq, but worse than BBSeq, PoissonSeq, BaySeq, voom 
and edgeR, the latter two being the best.  Of course DSS may do better in 
other simulation scenarios, and it may have been improved since our 
simulations were done in April 2012.  I don't expect you to believe this 
until we publish our results, but it is not my intention to change the 
methods used in edgeR with every new published paper.

Best wishes
Gordon

> thanks,
>
>
> -- output of sessionInfo():
>
> any

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