[BioC] segmentation aCGH data

[jhs1jjm at leeds.ac.uk]

Hi Sean,

As its 2 colour so I'm looking at relative amounts wouldn't that mean I
wouldn't see copy number variants, would they not be in both my
samples? I was also pondering the advantages of using R and
bioconductor, vs say Agilent's z score, for the purposes of my
discussion. Is the simple answer simply a flexible approach to these
matters? Also if possible could you expand a bit in regards to the
single probes argument.

Thanks for the input

John

Quoting Sean Davis <sdavis2 at mail.nih.gov> on Wed 10 Oct 2007 15:36:21
BST:

> jhs1jjm at leeds.ac.uk wrote:
> > Hi list,
> >
> > I've been looking at 3*44k and 2*244k agilent CGH arrays. To date
> I've
> > used limma to read in the processed signals (no background
> correction
> > or normalization as this has been done), then the DNAcopy package
> for
> > segmentation as well as the snapCGH package to employ other
> > segmentation methods rather than use each segmentation package
> > individually.
> >
> > Firstly using the DNAcopy segmentation I can see a significant
> pattern
> > across my 3*44k arrays which disappears when I perform the step to
> > remove unnecessary change points due to trends in the data. As
> these
> > are in the same locations across the 3 arrays then is it likely
> that
> > this is biologically significant rather than being a trend?
> Obviously
> > others do not have a definitive answer for this but I wondered if
> > anyone had seen similar results in a different scenario.
>
> What you are describing could be technical in nature or
> copy-number-variants.  You will probably need to review those regions
> for known copy-number-variants and also look at the quality control
> metrics for those probes.  Unfortunately, segmentation is not "the
> final
> answer" to CGH analysis--there has to be some curation (either manual
> or
> automated) to find the regions of greatest interest and remove the
> regions that are likely not associated with the disease state.
>
> > Additionally I'm wondering what segmentation methods people have
> tended
> > to employ. The heterogeneous nature of my data means that I need to
> > identify  single probe as well as larger region aberrations and I'd
> > read that the CBS algorithm is not particular suited to doing this?
> > Apologies   if this is a bit vague.
>
> Single probes are problematic and require validation using another
> technology or array platform, in my opinion.
>