Bioinformatics Advance Access originally published online on January 28, 2009
Bioinformatics 2009 25(6):722-728; doi:10.1093/bioinformatics/btp063
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A flexible rank-based framework for detecting copy number aberrations from array data
1Department of Genetics, Case Western Reserve University, Cleveland, OH 44106, 2Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195, 3The Broad Institute of Harvard and MIT, Cambridge, MA 02141, USA, 4Max Planck Institute for Neurological Research with Klaus-Joachim-Zülch Laboratories of the Max Planck Society and 5The Medical Faculty of the University of Köln, Köln, Germany
*To whom correspondence should be addressed.
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Abstract |
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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 article, 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 reasonable quality.
Conclusions: Our flexible rank-based framework is suitable for multiple platforms including single nucleotide polymorphism arrays and array comparative genomic hybridization, 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 data are available at Bioinformatics online.
Associate editor: Alex Bateman
Received on October 9, 2008; revised on December 19, 2008; accepted on January 26, 2009
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