Journal
BIOSTATISTICS
Volume 6, Issue 1, Pages 45-58Publisher
OXFORD UNIV PRESS
DOI: 10.1093/biostatistics/kxh017
Keywords
array CGH; CLAC; cluster; DNA copy number
Funding
- DIVISION OF HEART AND VASCULAR DISEASES [N01HV028183] Funding Source: NIH RePORTER
- NATIONAL CANCER INSTITUTE [R01CA097139] Funding Source: NIH RePORTER
- NCI NIH HHS [R01CA97139] Funding Source: Medline
- NHLBI NIH HHS [N01-HV-28183] Funding Source: Medline
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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.
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