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Biostatistics 2005 6(1):45-58; doi:10.1093/biostatistics/kxh017
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Biostatistics Vol. 6 No. 1 © Oxford University Press 2005; all rights reserved.

A method for calling gains and losses in array CGH data

Pei Wang

Department of Statistics, Stanford University, CA, 94305, USA wp57{at}stanford.edu

Young Kim and Jonathan Pollack

Department of Pathology, Stanford University, CA, 94305, USA

Balasubramanian Narasimhan

Department of Statistics, Stanford University, CA, 94305, USA

Robert Tibshirani

Departments of Health, Research & Policy, and Statistics, Stanford University, CA, 94305, USA

Array CGH is a powerful technique for genomic studies of cancer. It enables one to carry out genome-wide screening for regions of genetic alterations, such as chromosome gains and losses, or localized amplifications and deletions. In this paper, we propose a new algorithm ‘Cluster along chromosomes’ (CLAC) for the analysis of array CGH data. CLAC builds hierarchical clustering-style trees along each chromosome arm (or chromosome), and then selects the ‘interesting’ clusters by controlling the False Discovery Rate (FDR) at a certain level. In addition, it provides a consensus summary across a set of arrays, as well as an estimate of the corresponding FDR. We illustrate the method using an application of CLAC on a lung cancer microarray CGH data set as well as a BAC array CGH data set of aneuploid cell strains.

Keywords: Array CGH; CLAC; Cluster; DNA copy number; FDR


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