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

TLDR

Mass spectrometry coupled with online separation is widely used for differential and quantitative profiling in metabolomics and proteomics, supporting systems biology, functional genomics, and biomarker discovery, yet improved data‑processing methods remain a key challenge. This work introduces MZmine 2, a new generation of an open‑source toolbox for mass‑spectrometry data processing. MZmine 2 is built on a modular architecture that separates core functions from processing modules, offers high‑resolution spectra support, embedded visualization for parameter tuning, and new features such as database‑based peak identification, MSn support, enhanced isotope pattern analysis, scatter‑plot visualization, and a RANSAC‑based peak‑list alignment algorithm evaluated against other methods. MZmine 2 is freely available under a GNU GPL license at http://mzmine.sourceforge.net/, and its current version handles large data batches and has been successfully applied to both targeted and non‑targeted metabolomic studies.

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.