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Application of the cghRA framework to the genomic characterization of Diffuse Large B-Cell Lymphoma
- 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.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Polymorphism Detection
Computer science
Interface (Java)
[SDV]Life Sciences [q-bio]
Copy number analysis
Genomics
computer.software_genre
Biochemistry
Genome
03 medical and health sciences
0302 clinical medicine
Humans
Molecular Biology
ComputingMilieux_MISCELLANEOUS
Comparative Genomic Hybridization
Polymorphism, Genetic
Computer Science Applications
Computational Mathematics
030104 developmental biology
Computational Theory and Mathematics
030220 oncology & carcinogenesis
Lymphoma, Large B-Cell, Diffuse
Data mining
computer
Algorithms
Software
Comparative genomic hybridization
Subjects
Details
- ISSN :
- 13674811 and 13674803
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....77bca7e30abac134276a4bd871acf885