Copy Number Analysis across multiple SNP array plaforms
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Ed Schwalbe ▴ 20
@ed-schwalbe-5262
Last seen 10.2 years ago
Dear list, I have SNP array data run on three platforms: Affymetrix SNP6 (n=~250), Illumina OmniExpress (fresh frozen DNA) (n=12), Illumina OmniExpress FFPE (n=48). Since the cancer I work on is comparatively rare, many of our diagnostic samples are available only as paraffin blocks, so the arrival of Illumina's OmniExpress arrays which were reported to work with FFPE material was most welcome (just FYI, 40/48 FFPE arrays have passed Illumina's own QC procedures available within GenomeStudio). What I would like to do is to test for recurrent copy number abnormalities across the three platforms, in a way that minimises platform-dependent bias as much as possible. I posted the same question to BioStars and was directed to this paper: A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods http://bioinformatics.oxfordjournals.org/content/25/7/861.short However, on investigating this approach, it was clear that this is geared towards increasing resolution through estimates of CN using multiple platforms on the same sample, and doesn't consider extending this to non-repeated samples. My latest thought is to at least ensure consistent normalisation and segmentation, firstly by using CRLMM to normalise each platform, although the metadata for the omni express FFPE platform is not yet available for me to do this, followed by some form of segmentation (CBS, GLAD?). So, after that lengthy introduction, my two questions are: 1) Is there any possibility of releasing a CRLMM metadata file for the Omni Express FFPE platform? 2) Does anyone have any better ideas of how I might integrate these data? Thanks for any guidance you might give! Best wishes, Ed sessionInfo() R version 2.15.0 (2012-03-30) Platform: x86_64-pc-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United Kingdom.1252 [2] LC_CTYPE=English_United Kingdom.1252 [3] LC_MONETARY=English_United Kingdom.1252 [4] LC_NUMERIC=C [5] LC_TIME=English_United Kingdom.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] BiocInstaller_1.4.4 loaded via a namespace (and not attached): [1] tools_2.15.0
SNP Cancer crlmm ffpe SNP Cancer crlmm ffpe • 1.7k views
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Djork Clevert ▴ 210
@djork-clevert-422
Last seen 10.2 years ago
Hi Ed, take a look at our cn.farms package which was published in Nucleic Acids Research (http://nar.oxfordjournals.org/content/early/2011/04/12 /nar.gkr197.abstract) last year. The current version supports only Affymetrix array, but it you are interested in using it I can send you a version that works also with Illumina's OmniExpress array. Cheers, Okko -- dipl.-inf. djork clevert | gleimstr. 13a | d-10437 berlin e: okko@clevert.de p: +49.30.4432 4702 f: +49.30.6883 5307 Am 01.05.2012 um 12:33 schrieb Ed Schwalbe: > Dear list, > > I have SNP array data run on three platforms: Affymetrix SNP6 (n=~250), Illumina OmniExpress (fresh frozen DNA) (n=12), Illumina OmniExpress FFPE (n=48). > > Since the cancer I work on is comparatively rare, many of our diagnostic samples are available only as paraffin blocks, so the arrival of Illumina's OmniExpress arrays which were reported to work with FFPE material was most welcome (just FYI, 40/48 FFPE arrays have passed Illumina's own QC procedures available within GenomeStudio). > > What I would like to do is to test for recurrent copy number abnormalities across the three platforms, in a way that minimises platform-dependent bias as much as possible. > > I posted the same question to BioStars and was directed to this paper: > > A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods http://bioinformatics.oxfordjournals.org/content/25/7/861.short > > However, on investigating this approach, it was clear that this is geared towards increasing resolution through estimates of CN using multiple platforms on the same sample, and doesn't consider extending this to non-repeated samples. > > My latest thought is to at least ensure consistent normalisation and segmentation, firstly by using CRLMM to normalise each platform, although the metadata for the omni express FFPE platform is not yet available for me to do this, followed by some form of segmentation (CBS, GLAD?). > > So, after that lengthy introduction, my two questions are: > > 1) Is there any possibility of releasing a CRLMM metadata file for the Omni Express FFPE platform? > 2) Does anyone have any better ideas of how I might integrate these data? > > Thanks for any guidance you might give! > > Best wishes, > > Ed > > > sessionInfo() > > R version 2.15.0 (2012-03-30) > Platform: x86_64-pc-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_United Kingdom.1252 > [2] LC_CTYPE=English_United Kingdom.1252 > [3] LC_MONETARY=English_United Kingdom.1252 > [4] LC_NUMERIC=C > [5] LC_TIME=English_United Kingdom.1252 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] BiocInstaller_1.4.4 > > loaded via a namespace (and not attached): > [1] tools_2.15.0 > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor [[alternative HTML version deleted]]
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