[BioC] Newbie methylation and stats question

[Gustavo Fernández Bayón]

Hi Tim.  

Thank you for your answer. I'll try to "defend" myself the best I can below. ;)  


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Enviado con Sparrow (http://www.sparrowmailapp.com/?sig)


El martes 19 de junio de 2012 a las 16:20, Tim Triche, Jr. escribió:

> Look up Andrew Jaffe and Rafa Irizarry's paper on "bump hunting" for regional differences.  

I think both Mark and you have agreed on the paper. That surely is a good point for making me read it thoroughly.   
> Or run a smooth over it (caveat: I just wrote smoothing "the way I want it" yesterday, after being provoked by a collaborator, so you might have to use lumi).

I am not sure if I understand what you are trying to tell me here. ;) Sorry. I know lumi, although I thought it covered only the necessary stages until normalization of data.
> The function "dmrFinder" in the "charm" package is specifically meant for this sort of thing.

I had looked at the charm Vignette in the past few days, but thought it was designed for technology different from ours. For me, sometimes it is difficult to just "understand" the goals or targets of different packages. I am currently biocLite'ing it while I am writing this, so I'll take a look to dmrFinder and tell you.    
> Also, if you're doing linear tests, be careful with normalization,  

I thought (too naively, I guess) that, when given the beta values, everything was normalized. I.e., that I was safe unless I worked with raw data.
> mask your SNPs and chrX probes,  

I am currently doing something well :) At least, the chrX part. How could I mask the SNP's?  
> and maybe use M-values (logit(beta)) for the task.  

Yes, that's a point I was reading a lot lately. As far as I think I have understood, M-values have better statistical properties for spotting DMR's, haven't they?  
> The latter is more important for epidemiological datasets than something like cancer, where every single interesting result from M-value testing has been reproduced using untransformed beta values when I ran comparisons (e.g. HELP hg17 methylation differences for IDH1/2 mutants vs. Illumina hm450 differences for IDH1/2 mutants, the complete absence of any differences for TET2 mutants regardless of platform, etc.)

Well. I have to assume that I do not understand completely what you have written above. ;) Don't worry, it's not your problem. I'm sure it's mine. I am sometimes quite overwhelmed by the huge amount of information in this field.  
>  
> Mark Robinson just chimed in, I see. Probably a good idea to read his reply carefully as well.

I have done. And both your answer and his have been very helpful, constructive,  and kind. Thank you very much.   

Regards,

Gustavo