MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

By Tomás Pluskal, Sandra Castillo, Alejandro Villar-Briones, Matej Oresic. BMC Bioinformatics, 2010

817 citations recorded by the source corpus.

BackgroundMass 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.ResultsA 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.ConclusionsMZmine 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.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/ac1f5bdc2035fb0c0313ec34262be10d6c5ba427

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Citations in the corpus

The Dynamics of the Human Infant Gut Microbiome in Development and in Progression towards Type 1 Diabetes (2015, neutral): “Raw UPLC-MS and GC×GC-TOFMS data were processed with MZmine 2 (Pluskal et al., 2010) and Guineu (Castillo et al.”
American Gut: an Open Platform for Citizen Science Microbiome Research (2018, neutral): “Selective feature extraction was performed with open source 749 MZmine2 software (98).”
Analytical Methods in Untargeted Metabolomics: State of the Art in 2015 (2015, neutral): “Another common alignment method used in MS is the RANSAC algorithm (Pluskal et al., 2010).”
MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis (2018, methodology): “A number of excellent methods have been developed to deal with the first two tasks (26,27), which typically yield a list of ‘clean’ MS peaks.”