Bioconductor: Open software development for computational biology and bioinformatics

Robert C. Gentleman, Department of Biostatistical Sciences, Dana Farber Cancer Institute
Vincent J. Carey, Channing Laboratory, Brigham and Women's Hospital
Douglas J. Bates, Department of Statistics, University of Wisconsin, Madison
Benjamin M. Bolstad, Division of Biostatistics, University of California, Berkeley
Marcel Dettling, Seminar for Statistics, ETH, Zurich, CH
Sandrine Dudoit, Division of Biostatistics, University of California, Berkeley
Byron Ellis, Department of Statistics, Harvard University
Laurent Gautier, Center for Biological Sequence Analysis, Technical University of Denmark, DK
Yongchao Ge, Department of Biomathematical Sciences, Mount Sinai School of Medicine
Jeff Gentry, Department of Biostatistical Sciences, Dana Farber Cancer Institute
Kurt Hornik, Computational Statistics Group, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, AT
Torsten Hothorn, Institut fuer Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universitat Erlangen-Nurnberg, DE
Wolfgang Huber, Department for Molecular Genome Analysis (B050), German Cancer Research Center, Heidelberg, DE
Stefano Iacus, Department of Economics, University of Milan, IT
Rafael Irizarry, Department of Biostatistics, Johns Hopkins University
Friedrich Leisch, Institut für Statistik und Wahrscheinlichkeitstheorie, Technische Universität Wien, AT
Cheng Li, Department of Biostatistical Sciences, Dana Farber Cancer Institute
Martin Maechler, Seminar for Statistics, ETH, Zurich, CH
Anthony J. Rossini, Department of Medical Education and Biomedical Informatics, University of Washington
Guenther Sawitzki, Statistisches Labor, Institut fuer Angewandte Mathematik, DE
Colin Smith, Department of Molecular Biology, The Scripps Research Institute, San Diego
Gordon K. Smyth, Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, Melbourne, AU
Luke Tierney, Department of Statistics and Actuarial Science, University of Iowa
Yee Hwa Yang, Center for Bioinformatics and Molecular Biostatistics, Univerisity of California, San Francisco
Jianhua Zhang, Department of Biostatistical Sciences, Dana Farber Cancer Institute

Abstract

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. We detail some of the design decisions, software paradigms and operational strategies that have allowed a small number of researchers to provide a wide variety of innovative, extensible, software solutions in a relatively short time. The use of an object oriented programming paradigm, the adoption and development of a software package system, designing by contract, distributed development and collaboration with other projects are elements of this project's success. Individually, each of these concepts are useful and important but when combined they have provided a strong basis for rapid development and deployment of innovative and flexible research software for scientific computation. A primary objective of this initiative is achievement of total remote reproducibility of novel algorithmic research results.