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Open AccessJournal ArticleDOI

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

TLDR
A new generation of a popular open-source data processing toolbox, MZmine 2 is introduced, suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
Abstract
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. 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. 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.

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Journal ArticleDOI

Feature-based molecular networking in the GNPS analysis environment.

Louis-Félix Nothias, +87 more
- 24 Aug 2020 - 
TL;DR: Feature-based molecular networking (FBMN) as discussed by the authors is an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools.
Journal ArticleDOI

Novel Theranostic Opportunities Offered by Characterization of Altered Membrane Lipid Metabolism in Breast Cancer Progression

TL;DR: Analyzing the global lipid profiles of breast cancer, integrating the results to protein expression, and validate the findings by functional experiments imply that phospholipids may have diagnostic potential as well as that modulation of their metabolism may provide therapeutic opportunities in breast cancer treatment.
Reference EntryDOI

LC‐MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

TL;DR: MAVEN as mentioned in this paper is an open-source software program for interactive processing of LC-MS-based metabolomics data, which enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data.
Journal ArticleDOI

The food metabolome: a window over dietary exposure

TL;DR: Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data.
Journal ArticleDOI

Mass spectral databases for LC/MS- and GC/MS-based metabolomics: state of the field and future prospects

TL;DR: The main characteristics of the mass spectral databases currently used in MS-based metabolomics are reviewed in this paper, underlining their advantages and limitations, and the overlap of compounds with MSn (n ≥ 2) spectra from authentic chemical standards in most public and commercial databases has been calculated for the first time.
References
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Journal ArticleDOI

KEGG: Kyoto Encyclopedia of Genes and Genomes

TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Journal ArticleDOI

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Journal ArticleDOI

Probability-based protein identification by searching sequence databases using mass spectrometry data.

TL;DR: A new computer program, Mascot, is presented, which integrates all three types of search for protein identification by searching a sequence database using mass spectrometry data, and the scoring algorithm is probability based.
Journal ArticleDOI

Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting

TL;DR: Locally weighted regression as discussed by the authors is a way of estimating a regression surface through a multivariate smoothing procedure, fitting a function of the independent variables locally and in a moving fashion analogous to how a moving average is computed for a time series.
Journal ArticleDOI

METLIN: a metabolite mass spectral database.

TL;DR: METLIN includes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrumetry (MS/MS) Spectra, and LC/MS data.
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