SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets

Background: Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease. Results: We propose a supervised algorithm for the analysis of aCGH data and the identification of regions of chromosomal alteration (SIRAC). We first determine the DNA-probes that are important to distinguish the classes of interest, and then evaluate in a systematic and robust scheme if these relevant DNA-probes are closely located, i.e. form a region of amplification/deletion. SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters. Conclusion: We illustrate the features of the algorithm with the use of a simple artificial dataset...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Carmen Lai, Hugo M. Horlings, Marc J. van de Vijver, Eric H. van Beers, Petra M. Nederlof, Lodewyk F. A. Wessels, Marcel J. T. Reinders
• Keywords: ACGH, Array Comparative Genome, BMCBI 2007, Cancer