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Bioinformatics Advance Access published online on January 28, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp063
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A Flexible Rank-Based Framework for DetectingCopy Number Aberrations from Array Data

Thomas LaFramboise 1,2,*, Wendy Winckler 3 and Roman K Thomas 4

1Department of Genetics, Case Western Reserve University, Cleveland, OH, 44106, USA
2Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
3The Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02141, USA
4Max-Planck Institute for Neurological Research, Cologne, Germany

*To whom correspondence should be addressed. Thomas LaFramboise, E-mail: Thomas.LaFramboise{at}case.edu


  Abstract

Motivation: DNA copy number aberration – both inherited and sporadic – is a significant contributor to a variety of human diseases. Copy number characterization is therefore an area of intense research. Probe hybridization-based arrays are important tools used to measure copy number in a high-throughput manner.

Results: In this paper, we present a simple but powerful nonparametric rank-based approach to detect deletions and gains from raw array copy number measurements. We use three different rank-based statistics to detect three separate molecular phenomena - somatic lesions, germline deletions, and germline gains. The approach is robust and rigorously grounded in statistical theory, thereby enabling the meaningful assignment of statistical significance to each putative aberration. We demonstrate the flexibility of our approach by applying it to data from three different array platforms. We show that our method compares favorably with established approaches by applying it to published well-characterized samples. Power simulations demonstrate exquisite sensitivity for array data of rea-sonable quality.

Conclusions: Our flexible rank-based framework is suitable for multiple platforms including SNP arrays and array CGH, and can reliably detect gains or losses of genomic DNA, whether inherited, de novo, or somatic.

Availability: An R package RankCopy containing the methods described here, and is freely available from the author's web site (http://mendel.gene.cwru.edu/laframboiselab/).

Contact: Thomas.LaFramboise{at}case.edu

Supplementary information: Supplementary Methods and Supplementary Figures are available.

Associate Editor: Dr. Alex Bateman

Received on October 9, 2008; revised on December 19, 2008; accepted on January 26, 2009

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