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MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data
G0 Cell Unit, Okinawa Institute of Science and Technology (OIST), Onna, Okinawa, Japan.
Quantitative Biology and Bioinformatics, VTT Technical Research Centre of Finland, Espoo, Finland.
G0 Cell Unit, Okinawa Institute of Science and Technology (OIST), Onna, Okinawa, Japan.
Quantitative Biology and Bioinformatics, VTT Technical Research Centre of Finland, Espoo, Finland.ORCID iD: 0000-0002-2856-9165
2010 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 11, 395Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2.

RESULTS: A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms.

CONCLUSIONS: MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/. The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.

Place, publisher, year, edition, pages
BioMed Central, 2010. Vol. 11, 395
National Category
Microbiology in the medical area Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
URN: urn:nbn:se:oru:diva-59352DOI: 10.1186/1471-2105-11-395ISI: 000281442200001PubMedID: 20650010Scopus ID: 2-s2.0-77954772536OAI: oai:DiVA.org:oru-59352DiVA: diva2:1135856
Note

Funding Agencies:

Okinawa Institute of Science and Technology Promotion Corporation  

EU  FP7-KBBE-222639 

Available from: 2017-08-24 Created: 2017-08-24 Last updated: 2017-09-04Bibliographically approved

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