Bioinformatics Advance Access first published online on September 13, 2005
This version published online on September 14, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti677
1 Center for Biological Sequence Analysis, Technical University of Denmark, Kgs. Lyngby, Denmark
* 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 study 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, resulting in an interpretable set of copy number levels, and thus facilitating identification of copy number alterations in each genome. Availability: http://www.bioconductor.org. Supplementary Information: http://www.cbs.dtu.dk/~hanni/aCGH/.
Received July 5, 2005
Revised September 8, 2005
Accepted September 8, 2005
Article
A comparison study: applying segmentation to array CGH data for downstream analyses
2 Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, USA
Jane Fridlyand, E-mail: jfridlyand{at}cc.ucsf.edu
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