[BioC] DESeq normalization

[Simon Anders]

Hi Sudeep

On 2012-08-01 11:47, sudeep s wrote:

> I was checking DESeq normalization success for my samples following
> the suggestions in this post :
> https://stat.ethz.ch/pipermail/bioconductor/2010-October/035933.html.
> I observed that filtering down to the genes that are present in both
> case and control samples improved normalization  (visualized by
> plotting as per the post), but for a few samples ,say  3 samples
> these procedures did not help, and I tried calculating shorth
> estimator (again as per the post) and this did n't help either. My
> question is what should I follow for the normalization of these
> samples ?

You would need to tell us what exactly you did not like about the 
histograms.

Anyway, I revised my opinion a bit, and I now think that MA plots are 
mroe helpful.

Starting as in the post that you cited, plot an MA plot instead of a 
histogram, with

plot( geomeans, log2( counts(cds)[,j] / geomeans ), log="x",
    pch=".", col="#00000060" )
abline( h=log2( sizeFactors(cds)[ j ] ), col="red" )


   Simon