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.

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Acknowledgements

We thank all contributors to the Bioconductor and R projects. Bioconductor is supported by the National Human Genome Research Institute of the US National Institutes of Health (U41HG004059 to M.M.). Additional support is from the US National Science Foundation (1247813 to M.M.) and the European Commission FP7 project RADIANT (to W.H.). A. Bruce provided graphics support for Figure 2.

Author information

Affiliations

  1. European Molecular Biology Laboratory, Heidelberg, Germany.

    • Wolfgang Huber
    • , Simon Anders
    • , Andrzej K Oleś
    •  & Alejandro Reyes
  2. Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.

    • Vincent J Carey
  3. Harvard School of Public Health, Boston, Massachusetts, USA.

    • Vincent J Carey
    • , Rafael A Irizarry
    •  & Michael I Love
  4. Genentech, South San Francisco, California, USA.

    • Robert Gentleman
    •  & Michael Lawrence
  5. Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

    • Marc Carlson
    • , Valerie Obenchain
    • , Hervé Pagès
    • , Paul Shannon
    • , Dan Tenenbaum
    •  & Martin Morgan
  6. Department of Medical Genetics, School of Medical Sciences, State University of Campinas, Campinas, Brazil.

    • Benilton S Carvalho
  7. Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA.

    • Hector Corrada Bravo
  8. Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

    • Sean Davis
  9. Department of Biochemistry, University of Cambridge, Cambridge, UK.

    • Laurent Gatto
  10. Institute for Integrative Genome Biology, University of California, Riverside, Riverside, California, USA.

    • Thomas Girke
  11. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

    • Raphael Gottardo
  12. Novartis Institutes for Biomedical Research, Basel, Switzerland.

    • Florian Hahne
  13. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA.

    • Kasper D Hansen
  14. Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA.

    • Kasper D Hansen
  15. Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

    • Rafael A Irizarry
    •  & Michael I Love
  16. Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

    • James MacDonald
  17. Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.

    • Gordon K Smyth
  18. Department of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia.

    • Gordon K Smyth
  19. School of Urban Public Health at Hunter College, City University of New York, New York, New York, USA.

    • Levi Waldron

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The authors declare no competing financial interests.

Corresponding author

Correspondence to Wolfgang Huber.

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DOI

https://doi.org/10.1038/nmeth.3252

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