On Fri, Jul 23, 2010 at 12:51 PM, Paul Geeleher <paulgeeleher@gmail.com>wrote:

> Thanks for the replies guys,
>
> Sean, we have 5 disease samples and 5 control samples. Each array has
> 244k reporters located in CpG islands, averaging about 8 reporters per
> CpG island.
>
>
So, why not generate a 10 x 244k matrix or 10 x 30k matrix if you summarize
over CpG island and then apply a hypothesis test of your choice (which might
need to be nonparametric, even) to the data?  The value associated with each
probe per sample could be either a raw value (after "appropriate
normalization") or it could be derived from a number of ChIP-chip like
analysis packages (ACME, tilingarray, etc.).

Sean


> Jinyan, doesn't MEDME require some kind of calibration experiment?
> Needless to say this hasn't been done and it's unlikely that there is
> money there to do it.
>
> Paul.
>
> On Fri, Jul 23, 2010 at 7:02 PM, Sean Davis <sdavis2@mail.nih.gov> wrote:
> > Hi, Paul.  How many samples do you have?  And what are the sizes of the
> > groups?
> >
> > It seems to me that you have for each probe a number.  You could do
> > probewise testing between groups, or you could do some summarization
> first
> > and then hypothesis testing.  In any case, there are a number of ways to
> > arrive at an n x p matrix where standard statistical tools could be used.
> >
> > Sean
> >
> > On Jul 23, 2010 11:54 AM, "Paul Geeleher" <paulgeeleher@gmail.com>
> wrote:
> >
> > I understand your approach but the main problem I'd see with such a
> > thresholding approach is that you are highly likely to find regions
> > that are just below the cutoff to be called "methylated" in one
> > phenotype and just above the threshold in the other phenotype. Thus
> > most likely not differentially methylated at all. Do you see what I
> > mean?
> >
> > Perhaps some kind of approach that labels each reporter as having a
> > probability of methylation (and hence a probability of unmethylation),
> > which can be compared across samples of a given phenotype to give a
> > probability of all reporters being methylated/unmethylated in each
> > phenotype, then compares these probabilities between phenotypes to
> > give a probability of "differential methylation". That's just off the
> > top of my head, I think it makes sense, but I'm presuming nothing like
> > that has actually been implemented?
> >
> > Paul.
> >
> > On Fri, Jul 23, 2010 at 6:45 PM, Steve Lianoglou
> > <mailinglist.honeypot@gmail.com> wrote:
> >> Hi,
> >>
> >> ...
> >
> > --
> > Paul Geeleher
> > School of Mathematics, Statistics and Applied Mathematics
> > National University of I...
> >
> > Bioconductor mailing list
> > Bioconductor@stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/bioco...
>
>
>
> --
> Paul Geeleher
> School of Mathematics, Statistics and Applied Mathematics
> National University of Ireland
> Galway
> Ireland
> --
> www.bioinformaticstutorials.com
>
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