Processing Metabolomics and Proteomics Data with Open Software: A Practical Guide
CHAPTER 6: OpenMS and KNIME for Mass Spectrometry Data Processing
Published:16 Mar 2020
Special Collection: 2020 ebook collection
Oliver Alka, Timo Sachsenberg, Leon Bichmann, Julianus Pfeuffer, Hendrik Weisser, Samuel Wein, Eugen Netz, Marc Rurik, Oliver Kohlbacher, Hannes Röst, 2020. "OpenMS and KNIME for Mass Spectrometry Data Processing", Processing Metabolomics and Proteomics Data with Open Software: A Practical Guide, Robert Winkler
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Computational mass spectrometry is plagued by a multitude of issues, including a heterogeneous software environment, complex workflows and proprietary tools. OpenMS addresses these challenges by providing robust open-source software for users and an open, well-designed software environment for developers. OpenMS is an open-source software C++ library for LC-MS data management and analyses using modern C++11. It offers an infrastructure for rapid development of mass spectrometry related software. OpenMS is free software available under the three clause BSD license. It comes with a variety of pre-built and ready-to-use tools for high-throughput Proteomics and Metabolomics data analysis (TOPPTools), covering most MS and LC-MS data processing and mining tasks, as well as visualization (TOPPView). OpenMS offers automated analyses for various quantitation protocols, including label-free quantitation, SILAC, iTRAQ, TMT, SRM, SWATH. It provides built-in algorithms for de novo identification and database search, as well as adapters to other tools like X!Tandem, Mascot, OMSSA, SIRIUS. It supports easy integration of OpenMS built tools into workflow engines like KNIME, Galaxy, WS-Pgrade, and TOPPAS. OpenMS supports the Proteomics Standard Initiative (PSI) formats for MS data including mzML, mzXML, mzIdentXML, pepXML. With pyOpenMS, OpenMS offers Python bindings to a large part of the OpenMS API to enable rapid algorithm development.