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

Greenman, C. D., Bignell, G., Butler, A., Edkins, S., Hinton, J., Beare, D., Swamy, S., Santarius, T., Chen, L., Widaa, S., Futreal, P. A. and Stratton, M. R. (2010) PICNIC: an algorithm to predict absolute allelic copy number variation with microarray cancer data. Biostatistics, 11 (1). pp. 164-175. ISSN 1465-4644

Full text not available from this repository. (Request a copy)

Abstract

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.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
?? RGCB ??
Faculty of Science > School of Biological Sciences
University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Analysis and models of genomic variation
Depositing User: Christopher Greenman
Date Deposited: 22 Jun 2011 12:01
Last Modified: 15 Aug 2018 16:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/30590
DOI: 10.1093/biostatistics/kxp045

Actions (login required)

View Item