1. Orchestrating high-throughput genomic analysis with Bioconductor
- Author
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Paul Shannon, Kasper D. Hansen, Sean Davis, Vincent J. Carey, Benilton S. Carvalho, Marc R. J. Carlson, Thomas Girke, Valerie Obenchain, Martin Morgan, Raphael Gottardo, Rafael A. Irizarry, Dan Tenenbaum, Hervé Pagès, Héctor Corrada Bravo, Alejandro Reyes, Michael I. Love, Robert Gentleman, James W. MacDonald, Simon Anders, Florian Hahne, Levi Waldron, Andrzej K. Oleś, Wolfgang Huber, Michael S. Lawrence, Gordon K. Smyth, Laurent Gatto, and UCL - SSS/DDUV - Institut de Duve
- Subjects
Computer science ,Interoperability ,Genomics ,Bioinformatics ,Biochemistry ,Article ,Scientific software ,Bioconductor ,03 medical and health sciences ,User-Computer Interface ,0302 clinical medicine ,Software ,Molecular Biology ,Throughput (business) ,030304 developmental biology ,0303 health sciences ,business.industry ,Extramural ,Gene Expression Profiling ,Computational Biology ,Cell Biology ,Data science ,High-Throughput Screening Assays ,030220 oncology & carcinogenesis ,Programming Languages ,business ,Biotechnology - Abstract
Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.
- Published
- 2015
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