[BioC] Sliding window t-test?

[Michal Okoniewski]

Hi Tim,

In the package rnaSeqMap we have implemented (also in C) the
Aumann-Lindell algorithm, which is
sort of slide-and-join algorithm on two windows across the chromosome and
finds the regions even when there are
some small gaps. The regions found by A-L are "irreducible" -see the paper
on theorems of this property - and thus overcome some limitations of a
single sliding window. Applying it to your data probably would require
some workaround, 
but you may check rnaSeqMap vignette and paper and the original paper of
Aumann and Lindell from 2003,
perhaps it will be of some use for you.


Cheers, 
Michal 




On 6/6/11 8:35 PM, "Tim Smith" <tim_smith_666 at yahoo.com> wrote:

>Hi,
>
>I was trying to analyze some methylation (illumina 27k) data. I have data
>for 18 
>cancer and 18 normal samples. I want to find out if certain regions show
>consistently higher methylation in cancer (as compared to normal). A
>t-test (and 
>then corrected for fdr) for individual probes does not reveal a
>statistically 
>significant difference between samples.
>
>
>Is there a way I can use a sliding window approach to see if there are
>consistently differentially methylated regions? Is there a R and/or
>bioconductor 
>package that does it? Or if not, which statistical methods would be most
>appropriate?
>
>Tim
>
>	[[alternative HTML version deleted]]
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at r-project.org
>https://stat.ethz.ch/mailman/listinfo/bioconductor
>Search the archives:
>http://news.gmane.org/gmane.science.biology.informatics.conductor