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Comparative and Functional Genomics
Volume 2009, Article ID 201325, 8 pages
Research Article

Analysis of Array-CGH Data Using the R and Bioconductor Software Suite

Hannover Medical School, Institute of Cell and Molecular Pathology, Carl-Neuberg-Str. 1, 30625 Hannover, Germany

Received 2 December 2008; Revised 8 May 2009; Accepted 5 June 2009

Academic Editor: Eivind Hovig

Copyright © 2009 Winfried A. Hofmann et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Array-based comparative genomic hybridization (array-CGH) is an emerging high-resolution and high-throughput molecular genetic technique that allows genome-wide screening for chromosome alterations. DNA copy number alterations (CNAs) are a hallmark of somatic mutations in tumor genomes and congenital abnormalities that lead to diseases such as mental retardation. However, accurate identification of amplified or deleted regions requires a sequence of different computational analysis steps of the microarray data. Results. We have developed a user-friendly and versatile tool for the normalization, visualization, breakpoint detection, and comparative analysis of array-CGH data which allows the accurate and sensitive detection of CNAs. Conclusion. The implemented option for the determination of minimal altered regions (MARs) from a series of tumor samples is a step forward in the identification of new tumor suppressor genes or oncogenes.