[BioC] Newbie methylation and stats question

[Gustavo Fernández Bayón]

Hi Mark.  

First of all, thank you for your kind answer. I am answering you below (or at least trying to). ;)  


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El martes 19 de junio de 2012 a las 16:17, Mark Robinson escribió:

> […]
> You can do differential analyses at the probe level or a regional level. An example of the latter (perhaps less popular or less established or less known) is:
> http://ije.oxfordjournals.org/content/41/1/200.abstract

I have just given it a super-fast read, and it seems very interesting. I am going to read it more carefully, and see if it can help me to understand better where I am standing. If I have got the idea right, the authors seem to do some kind of regression or model fitting using the methylation values against the (maybe relative) position of the probes, in order to detect contiguous regions where differential methylation exists. Am I right?  
> […]
> First of all, I feel this is an unusual comparison to make. Presumably, region A and region B are different regions of the genome - what does it mean if methylation levels in region A and B are different? Maybe you could expand on the biological question here?

Yes, of course. A fellow wants to prove that a given region is differentially methylated between two sets of individuals. She has 6 case and 5 control individuals, along with their methylation beta values for a given set of probes (small, around 27 subdivided among 4 regions). Visually, she is able to see that there is a difference in methylation between the control and case group and, what is more, that the differentiation occurs 99% of the time in a given region.  

She asked me for a statistic test, so she could have a p-value showing that, not only the two groups are differentially methylated, but also the methylation happens at exactly one region. Kind of a "how can I show that this region is different and the others aren't?"
>  
> Second, if this is the comparison you really want to make, what role do your n samples play here? Do you have cases and controls? It may be sensible to fit a model to allow you to decompose effects of case/control from those of interest (A/B). But again, this needs to be geared to your biological question, which I don't yet understand.

I don't know if the explanation above is helping.  Feel free to ask me anything you need. The biggest problem, I know, is that sometimes I do not know how to put all of this down to words. Well, I hope that is going to improve with time (I have been only in Bioinformatics for two months).  
>  
> Best,
> Mark

Regards,
Gustavo