[BioC] Variance stabilization of m-values

Gordon K Smyth smyth at wehi.EDU.AU
Fri Aug 3 01:19:38 CEST 2012

Use eBayes with trend=TRUE later in the pipeline, then variance 
stabilization may not be needed.


> Date: Wed, 1 Aug 2012 15:20:56 +0200
> From: Gustavo Fern?ndez Bay?n <gbayon at gmail.com>
> To: bioconductor at r-project.org
> Subject: [BioC] Variance stabilization of m-values
> Hi everybody.
> I am working with Illumina 450k methylation data. I am currently 
> cleaning a data set, getting rid of XY probes, etc? and I would like to 
> do a non-specific filtering and preserve only 20% of the probes, those 
> with the higher variability (as seen in Chapter 7 of the Bioconductor 
> Case Studies book).
> In the book, they create a meanSdPlot() and proceed as the variance is 
> not dependent on the mean (to a significant degree).
> Trying to follow that procedure, I have converted my beta values to 
> M-values, and then called meanSdPlot(). It shows, for my data, that 
> there is a relationship between mean and variance, i.e. the line with 
> the median is not horizontal. Of course, if I create a meanSdPlot with 
> the beta values, the effect is greater, due to their heteroscedasticity.
> Question: Is it correct to use a variance stabilization transformation 
> (as the one in justvsn) on the M-values in order to discard low-variance 
> probes?
> Any hint will be much appreciated.
> Regards,
> Gus

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