[BioC] Variance stabilization of m-values

[Gustavo Fernández Bayón]

Hi Gordon.  

Sorry for the late reply. I'll try your solution and see if it works. Fact is, maybe I was too alarmed about the graph, and the relationship is not that important.  

Thank you very much.
Gus



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El viernes 3 de agosto de 2012 a las 01:19, Gordon K Smyth escribió:

> Use eBayes with trend=TRUE later in the pipeline, then variance  
> stabilization may not be needed.
>  
> Gordon
>  
> > Date: Wed, 1 Aug 2012 15:20:56 +0200
> > From: Gustavo Fern?ndez Bay?n <gbayon at gmail.com (mailto:gbayon at gmail.com)>
> > To: bioconductor at r-project.org (mailto: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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