[Bioc-devel] methylumi - using M-value for quantifing methylation levels?

Hi, Sean and all,

I have a couple question. Recently some of the researchers that I are working with are showing interests in using M-value (log ratio of methylation and unmethylation intensities - -log2[(Cy5+1)/(Cy3+1)]) for quantifying methylation levels. A recent paper also indicates that it is a good idea to use M-value methods. Here is the link of the paper:

http://www.biomedcentral.com/1471-2105/11/587/abstract

I am wondering if you can add the M-value method to the  normalizeMethyLumiSet function. Below is the patch that I did to modify MethyLimiSet-class.R in your methylumi package.

My second question is that the normalization scheme in the methylumi package is not optimal for Illumina Infinium methylation assay.  Does anyone knows what normalization method is suitable for infinium data? 

--------- patch ---------
cwon2 at alpaca:~/proj/Rpacks/methylumi/R> diff MethyLumiSet-class.R MethyLumiSet-class_new.R
391c391
< normalizeMethyLumiSet <- function(x,beta.cuts=c(0.2,0.8),mapfun=c('atan','ratio'))
---

normalizeMethyLumiSet <- function(x,beta.cuts=c(0.2,0.8),mapfun=c('atan','log','ratio'))

432c432
<   if(mapfun=='atan') {
---

  if(mapfun=='atan')

434c434,438
<   } else {
---

  if(mapfun=='log')
    newbeta <- log2((cy5+1)/(cy3+1))

  if(mapfun=='ratio')

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<   }
---

Chao-Jen Wong 
Program in Computational Biology 
Division of Public Health Sciences 
Fred Hutchinson Cancer Research Center 
1100 Fairview Avenue N., M1-B514 
PO Box 19024 
Seattle, WA 98109 
206.667.4485 
cwon2 at fhcrc.org