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OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

  • Röst HL Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Sachsenberg T Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Aiche S Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Bielow C Berlin Institute for Medical Systems Biology, Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.
  • Weisser H Proteomic Mass Spectrometry, Wellcome Trust Sanger Institute, Hinxton, UK.
  • Aicheler F Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Andreotti S Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Ehrlich HC Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Gutenbrunner P Proteomic Mass Spectrometry, Wellcome Trust Sanger Institute, Hinxton, UK.
  • Kenar E Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Liang X International Max Planck Research School for Computational Biology and Scientific Computing (IMPRS-CBSC), Berlin, Germany.
  • Nahnsen S Quantitative Biology Center, University of Tübingen, Tübingen, Germany.
  • Nilse L Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany.
  • Pfeuffer J Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Rosenberger G Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Rurik M Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Schmitt U ID Scientific IT Services, ETH Zurich, Zurich, Switzerland.
  • Veit J Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Walzer M Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Wojnar D Quantitative Biology Center, University of Tübingen, Tübingen, Germany.
  • Wolski WE Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Schilling O Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany.
  • Choudhary JS Proteomic Mass Spectrometry, Wellcome Trust Sanger Institute, Hinxton, UK.
  • Malmström L Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Aebersold R Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Reinert K Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Kohlbacher O Department of Computer Science, University of Tübingen, Tübingen, Germany.
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  • 2016-08-31
Published in:
  • Nature methods. - 2016
Aging
Blood Proteins
Computational Biology
Electronic Data Processing
Humans
Mass Spectrometry
Molecular Sequence Annotation
Proteogenomics
Proteomics
Software
Workflow
English High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.
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  • English
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green
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https://sonar.ch/global/documents/181196
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