OpenMS

OpenMS is an open-source software framework for mass spectrometry data analysis, with a focus on proteomics and metabolomics. It provides a modular C++ library of algorithms and data structures for processing LC-MS and GC-MS data, along with a set of command-line tools and graphical utilities that enable end-to-end workflows. The software emphasizes reproducibility and scalability, enabling researchers to build and share analysis pipelines.

Key functionality includes data models for spectra, chromatograms, and identified features; preprocessing steps such as noise reduction and peak picking; feature detection and deconvolution; chromatographic alignment and retention-time normalization; feature-based quantification for label-free and labeling experiments; and support for downstream statistical analysis and visualization. OpenMS also supports integration with external sequence database search engines to perform identifications and transfer those identifications to features.

Knime and Python bindings: The project provides Python bindings (pyOpenMS) and offers interoperability with workflow environments such as KNIME, enabling users to assemble pipelines without extensive programming. The TOPP (The OpenMS Proteomics Pipeline) collection includes many command-line tools, and TOPPView provides data visualization for spectra and features.

Distribution and licensing: OpenMS is open-source software released under the Apache License 2.0 and maintained by a community of researchers and developers. It runs on major platforms including Linux, Windows, and macOS, and is widely used in academic settings to enable reproducible, large-scale MS data analysis.