mMass 3: A Cross-Platform Software Environment for Precise Analysis of Mass Spectrometric Data

Martin Strohalm*, Daniel Kavan§, Petr Novák§, Michael Volný and Vladimír Havlíček
Institute of Microbiology, Academy of Sciences of the Czech Republic, v.v.i., Vídeňská 1083, 142 20 Prague, Czech Republic, Institute of Chemical Technology, Technická 5, 166 28 Prague, Czech Republic, Department of Biochemistry, Faculty of Science, Charles University, Hlavova 8, 128 40 Prague, Czech Republic, and Department of Analytical Chemistry, Palacky University, 17.listopadu 12, 771 46 Olomouc, Czech Republic
Anal. Chem., 2010, 82 (11), pp 4648–4651
DOI: 10.1021/ac100818g
Publication Date (Web): May 13, 2010
Copyright © 2010 American Chemical Society
* To whom correspondence should be addressed. E-mail: strohalm@biomed.cas.cz., †

Academy of Sciences of the Czech Republic.

, ‡

Institute of Chemical Technology.

, §

Charles University.

,

Palacky University.

Abstract

While tools for the automated analysis of MS and LC-MS/MS data are continuously improving, it is still often the case that at the end of an experiment, the mass spectrometrist will spend time carefully examining individual spectra. Current software support is mostly provided only by the instrument vendors, and the available software tools are often instrument-dependent. Here we present a new generation of mMass, a cross-platform environment for the precise analysis of individual mass spectra. The software covers a wide range of processing tasks such as import from various data formats, smoothing, baseline correction, peak picking, deisotoping, charge determination, and recalibration. Functions presented in the earlier versions such as in silico digestion and fragmentation were redesigned and improved. In addition to Mascot, an interface for ProFound has been implemented. A specific tool is available for isotopic pattern modeling to enable precise data validation. The largest available lipid database (from the LIPID MAPS Consortium) has been incorporated and together with the new compound search tool lipids can be rapidly identified. In addition, the user can define custom libraries of compounds and use them analogously. The new version of mMass is based on a stand-alone Python library, which provides the basic functionality for data processing and interpretation. This library can serve as a good starting point for other developers in their projects. Binary distributions of mMass, its source code, a detailed user’s guide, and video tutorials are freely available from www.mmass.org.

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History

  • Published In Issue June 01, 2010
  • Article ASAPMay 13, 2010
  • Received: March 30, 2010
    Accepted: May 03, 2010

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