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Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics

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Journal of The American Society for Mass Spectrometry

Abstract

Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics. It provides modules for reading LC-MS/MS data, search engine output, protein sequence databases, theoretical prediction of retention times, electrochemical properties of polypeptides, mass and m/z calculations, and sequence parsing. Pyteomics is available under Apache license; release versions are available at the Python Package Index http://pypi.python.org/pyteomics, the source code repository at http://hg.theorchromo.ru/pyteomics, documentation at http://packages.python.org/pyteomics. Pyteomics.biolccc documentation is available at http://packages.python.org/pyteomics.biolccc/. Questions on installation and usage can be addressed to pyteomics mailing list: pyteomics@googlegroups.com

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Acknowledgments

The authors are grateful to their colleagues Dr. Irina Tarasova, Dr. Marina Pridatchenko, Anna Lobas, and Tatiana Perlova from the Institute for Energy Problems of Chemical Physics, as well as Dr. Achim Treumann from the University of Newcastle for useful discussions and suggestions on pyteomics functionality.

This work was supported in part by grants from the European Commission (FP7 project Prot-HiSPRA, #282506) and the Russian Basic Science Foundation (project #11-04-00515).

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Authors and Affiliations

  1. Department of Physics, Massachusetts Institute of Technology, Boston, MA, 02139, USA

    Anton A. Goloborodko

  2. Institute for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia

    Anton A. Goloborodko, Lev I. Levitsky, Mark V. Ivanov & Mikhail V. Gorshkov

  3. Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow region, 141700, Russia

    Anton A. Goloborodko, Lev I. Levitsky, Mark V. Ivanov & Mikhail V. Gorshkov

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  1. Anton A. Goloborodko
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  2. Lev I. Levitsky
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  3. Mark V. Ivanov
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  4. Mikhail V. Gorshkov
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Correspondence to Mikhail V. Gorshkov.

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Authors Goloborodko and Levitsky contributed equally to this work.

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Goloborodko, A.A., Levitsky, L.I., Ivanov, M.V. et al. Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics. J. Am. Soc. Mass Spectrom. 24, 301–304 (2013). https://doi.org/10.1007/s13361-012-0516-6

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  • DOI: https://doi.org/10.1007/s13361-012-0516-6

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