[BioC] segmentation aCGH data

jhs1jjm at leeds.ac.uk jhs1jjm at leeds.ac.uk
Wed Oct 10 15:52:17 CEST 2007


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.

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.

Thanks for any input,

John



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