Bioconductor is an open source, open development software project to provide tools for the analysis and comprehension of high-throughput genomic data. It is based primarily on the R programming language.
The Bioconductor release version is updated twice each year, and is appropriate for most users. There is also a development version, to which new features and packages are added prior to incorporation in the release. A large number of meta-data packages provide pathway, organism, microarray and other annotations.
The Bioconductor project started in 2001 and is overseen by a core team, based primarily at the Fred Hutchinson Cancer Research Center, and by other members coming from US and international institutions. It gained widespread exposure in a 2004 Genome Biology paper.
The broad goals of the Bioconductor project are:
- To provide widespread access to a broad range of powerful statistical and graphical methods for the analysis of genomic data.
- To facilitate the inclusion of biological metadata in the analysis of genomic data, e.g. literature data from PubMed, annotation data from Entrez genes.
- To provide a common software platform that enables the rapid development and deployment of extensible, scalable, and interoperable software.
- To further scientific understanding by producing high-quality documentation and reproducible research.
- To train researchers on computational and statistical methods for the analysis of genomic data.