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

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 a...

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Detalles Bibliográficos
Autores principales: Hofmann, Winfried A., Weigmann, Anja, Tauscher, Marcel, Skawran, Britta, Focken, Tim, Buurman, Reena, Wingen, Luzie U., Schlegelberger, Brigitte, Steinemann, Doris
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2728899/
https://www.ncbi.nlm.nih.gov/pubmed/19696946
http://dx.doi.org/10.1155/2009/201325
Descripción
Sumario: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.