OpenMS
OpenMS analyzes high-throughput mass spectrometry (MS) data to enable reproducible processing, quantitation, and interpretation of high-resolution MS datasets for life-science applications such as disease diagnosis, biomolecular structural elucidation, and cellular signaling network characterization.
Key Features:
- C++ and Python API: Provides programmatic access through APIs in C++ and Python for integration and extension of functionality.
- Standardized open data formats: Uses standardized open data formats to ensure interoperability and transparent analyses.
- Modular tool suite: Comprises over 185 tools covering data handling and complex quantitative mass spectrometric analyses that can be combined into workflows.
- Reproducible workflows: Supports construction and execution of reproducible data-processing workflows from modular components.
- TOPPAS workflow editor: Includes an integrated workflow editor (TOPPAS) for creating, editing, and executing data-processing pipelines.
- TOPPView visualization: Provides visualization tools (TOPPView) for inspection of raw and intermediate MS data to support quality control and troubleshooting.
- Quantitative analysis support: Enables sophisticated quantitative analyses of high-resolution MS datasets.
Scientific Applications:
- Disease diagnosis: Applied to MS-based analyses supporting biomarker discovery and diagnostic studies.
- Biomolecular structural elucidation: Used for processing MS data that inform structural characterization of biomolecules.
- Cellular signaling network characterization: Supports analysis of MS data for mapping and quantifying signaling pathways.
- Proteomics workflows: Enables construction and execution of proteomics pipelines for identification and quantitation.
- Quality control and troubleshooting: Facilitates inspection of raw and intermediate MS data for data quality assessment.
Methodology:
Provides C++ and Python APIs, utilizes standardized open data formats, offers a modular suite of over 185 tools, and includes TOPPAS for workflow construction and TOPPView for data visualization.
Topics
Collections
Details
- License:
- BSD-3-Clause
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- library, workflow
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- C++
- Added:
- 1/19/2016
- Last Updated:
- 4/30/2025
Operations
- Annotation
- Chromatographic alignment
- Comparison
- Data handling
- Deisotoping
- Formatting
- Isotope-coded protein label
- Label-free quantification
- Labeled quantification
- Mass spectra calibration
- Mass spectrum visualisation
- Parsing
- Peak detection
- Peptide identification
- Prediction and recognition (protein)
- Protein feature detection
- Protein identification
- Protein quantification
- Retention time prediction
- Spectral analysis
- Splitting
- Standardisation and normalisation
- Target-Decoy
- iTRAQ
Data Inputs & Outputs
Annotation
Inputs
Outputs
Publications
Röst HL, Sachsenberg T, Aiche S, Bielow C, Weisser H, Aicheler F, Andreotti S, Ehrlich H, Gutenbrunner P, Kenar E, Liang X, Nahnsen S, Nilse L, Pfeuffer J, Rosenberger G, Rurik M, Schmitt U, Veit J, Walzer M, Wojnar D, Wolski WE, Schilling O, Choudhary JS, Malmström L, Aebersold R, Reinert K, Kohlbacher O. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nature Methods. 2016;13(9):741-748. doi:10.1038/nmeth.3959. PMID:27575624.
Bertsch A, Gröpl C, Reinert K, Kohlbacher O. OpenMS and TOPP: Open Source Software for LC-MS Data Analysis. Methods in Molecular Biology. 2010. doi:10.1007/978-1-60761-987-1_23.