[BioC] Analysing DNA methylation microarrays in Bioconductor

[Steve Lianoglou]

Hi,

On Fri, Jul 23, 2010 at 1:35 PM, Paul Geeleher <paulgeeleher at gmail.com> wrote:
> Thanks for your reply Claus,
>
> What I've noticed however about these and every other tool I've found
> is that they seem to be able to characterize a methlyation pattern in
> a sample. I.e. say "this region appears to be methylated in this
> sample".
>
> What I'd like is something that can compare the methylation levels
> between the samples, basically outputting a probability that a
> region/reporter is methylated in one phenotype and unmethylated in the
> other. It would be great if anyone could point me towards such a tool,
> or confirm that it doesn't actually exist?

Well, I guess it's impossible to say that something *doesn't* exist
(cf. the black swan), but if you have tools that tell you "this region
is methylated" in a given sample, can't you do this yourself?

Say you use all of your replicate experiments to get a "golden answer"
for regions methylated in disease. and regions methylated in
"normals".

I could imagine storing such info in an IRanges object (or IRangesList
(one IRanges object for each chromosome), then just doing a
setdiff(disease, normal) to see which ranges are methylated in disease
and not normal.

Isn't that a start?

-steve

-- 
Steve Lianoglou
Graduate Student: Computational Systems Biology
 | Memorial Sloan-Kettering Cancer Center
 | Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact