Dissemin is shutting down on January 1st, 2025

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Oxford University Press, Bioinformatics, 19(33), p. 2977-2985, 2017

DOI: 10.1093/bioinformatics/btx309

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Application of the cghRA framework to the genomic characterization of Diffuse Large B-Cell Lymphoma

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

Abstract Motivation Although sequencing-based technologies are becoming the new reference in genome analysis, comparative genomic hybridization arrays (aCGH) still constitute a simple and reliable approach for copy number analysis. The most powerful algorithms to analyze such data have been freely provided by the scientific community for many years, but combining them is a complex scripting task. Results The cghRA framework combines a user-friendly graphical interface and a powerful object-oriented command-line interface to handle a full aCGH analysis, as is illustrated in an original series of 107 Diffuse Large B-Cell Lymphomas. New algorithms for copy-number calling, polymorphism detection and minimal common region prioritization were also developed and validated. While their performances will only be demonstrated with aCGH, these algorithms could actually prove useful to any copy-number analysis, whatever the technique used. Availability and implementation R package and source for Linux, MS Windows and MacOS are freely available at http://bioinformatics.ovsa.fr/cghRA. Supplementary information Supplementary data are available at Bioinformatics online.