Back to Search Start Over

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

Authors :
Abdelilah Bouzelfen
Sylvain Mareschal
Martin Figeac
Philippe Ruminy
Dominique Penther
Philippe Bertrand
Pierre-Julien Viailly
Christian Bastard
Marion Alcantara
Céline Villenet
Sydney Dubois
Fabrice Jardin
Hervé Tilly
Génomique et Médecine Personnalisée du Cancer et des Maladies Neuropsychiatriques (GPMCND)
Université de Rouen Normandie (UNIROUEN)
Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Plateforme de génomique fonctionnelle et structurelle [Lille]
Institut pour la recherche sur le cancer de Lille [Lille] (IRCL)-Université de Lille, Droit et Santé
Département d'Oncologie Génétique [Rouen] (CLCC Henri Becquerel)
Centre de Lutte Contre le Cancer Henri Becquerel Normandie Rouen (CLCC Henri Becquerel)
Source :
Bioinformatics, Bioinformatics, Oxford University Press (OUP), 2017, 33 (19), pp.2977-2985. ⟨10.1093/bioinformatics/btx309⟩
Publication Year :
2017
Publisher :
Oxford University Press (OUP), 2017.

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.

Details

ISSN :
13674811 and 13674803
Volume :
33
Database :
OpenAIRE
Journal :
Bioinformatics
Accession number :
edsair.doi.dedup.....77bca7e30abac134276a4bd871acf885