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Bioinformatics Advance Access originally published online on September 13, 2005
Bioinformatics 2005 21(22):4084-4091; doi:10.1093/bioinformatics/bti677
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org

A comparison study: applying segmentation to array CGH data for downstream analyses

Hanni Willenbrock 1 and Jane Fridlyand 2,*

1Center for Biological Sequence Analysis, Department of Biotechnology Building 208, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
2Department of Epidemiology and Biostatistics, University of California at San Francisco 2340 Sutter Street, N224, San Francisco, CA 94143, USA

*To whom correspondence should be addressed.

Motivation: Array comparative genomic hybridization (CGH) allows detection and mapping of copy number of DNA segments. A challenge is to make inferences about the copy number structure of the genome. Several statistical methods have been proposed to determine genomic segments with different copy number levels. However, to date, no comprehensive comparison of various characteristics of these methods exists. Moreover, the segmentation results have not been utilized in downstream analyses.

Results: We describe a comparison of three popular and publicly available methods for the analysis of array CGH data and we demonstrate how segmentation results may be utilized in the downstream analyses such as testing and classification, yielding higher power and prediction accuracy. Since the methods operate on individual chromosomes, we also propose a novel procedure for merging segments across the genome, which results in an interpretable set of copy number levels, and thus facilitate identification of copy number alterations in each genome.

Availability: http://www.bioconductor.org

Contact: jfridlyand{at}cc.ucsf.edu

Supplementary Information: http://www.cbs.dtu.dk/~hanni/aCGH/

Received on July 5, 2005; revised on September 8, 2005; accepted on September 12, 2005

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