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Biostatistics Advance Access published online on October 15, 2009
Biostatistics, doi:10.1093/biostatistics/kxp045
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

PICNIC: an algorithm to predict absolute allelic copy number variation with microarray cancer data

Chris D. Greenman*, Graham Bignell, Adam Butler, Sarah Edkins, Jon Hinton, Dave Beare, Sajani Swamy, Thomas Santarius, Lina Chen, Sara Widaa, P. Andy Futreal and Michael R. Stratton

Cancer Genome Project, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK cdg{at}sanger.ac.uk

* To whom correspondence should be addressed.

High-throughput oligonucleotide microarrays are commonly employed to investigate genetic disease, including cancer. The algorithms employed to extract genotypes and copy number variation function optimally for diploid genomes usually associated with inherited disease. However, cancer genomes are aneuploid in nature leading to systematic errors when using these techniques. We introduce a preprocessing transformation and hidden Markov model algorithm bespoke to cancer. This produces genotype classification, specification of regions of loss of heterozygosity, and absolute allelic copy number segmentation. Accurate prediction is demonstrated with a combination of independent experimental techniques. These methods are exemplified with affymetrix genome-wide SNP6.0 data from 755 cancer cell lines, enabling inference upon a number of features of biological interest. These data and the coded algorithm are freely available for download.

Keywords: Allelic; Cancer; Copy; Number; Somatic; Variation

Received July 23, 2008; revised November 10, 2009; revised March 16, 2009; revised April 27, 2009; revised July 13, 2009; revised August 24, 2009; accepted for publication September 15, 2009.


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