The open-source framework for Mass Spectrometry

Build sophisticated LC/MS data analysis tools with C++ or Python. Process large datasets at scale. Create high-performance algorithms. Join 1000+ researchers worldwide.

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What is OpenMS ?

OpenMS offers an open-source C++ library (+ Python bindings) for LC/MS data management, analysis and visualization. It empowers rapid development of mass spectrometry related software. OpenMS is freely available under the three clause BSD license and runs under Windows, macOS and Linux. The OpenMS members have a strong commitment to creating an open, inclusive, and positive community. Please read the OpenMS Code of Conduct for guidance on how to interact with others in a way that makes the community thrive.

New: WebApps

FLASHApp allows for interactive analysis and visualization of top-down proteomics data.

This app offers the powerful UmetaFlow pipeline for untargeted metabolomics in an accessible

OpenDIA is an interactive web app for Data-Independent Acquisition (DIA) analysis.

OpenDDA is a browser-based tool to identify and quantify proteins from DDA mass spectrometry data.

NuXL is a dedicated software package designed for the analysis of XL-MS (cross-linking mass spectrometry).

MHCQuant is a web application for analysis of MHC-bound peptides in immunopeptidomics studies.

TOPPView Lite is a web-based viewer for interactive visualization and exploration of mass spectrometry data.

NASEWEIS is a WebApp for the NucleicAcidSearch Engine. It allows for library searching of Oligonucleotides.

StreamSage is a web application for performing proteomics database searching in your browser.

OpenMS allows users to:

Run existing workflows

Run existing workflows for proteomics and metabolomics with OpenMS in KNIME.

Create your own workflows

Modify and create your own OpenMS workflows in Galaxy, KNIME and Nextflow.

Use OpenMS in Python

Enhance workflows with pyOpenMS scripts or develop novel methods using pyOpenMS

Advanced users / developers can use OpenMS to:

Analyze large datasets

Run workflows on very large datasets on powerful compute infrastructure

Create high-performance tools

Develop high-performance tools or algorithms with the C++ OpenMS library

Progress of 'loading spectra list':
-- done [took 0.19 s (CPU), 0.19 s (Wall)] --

Memory usage (loading MS data): 25 MB (working set delta), 25 MB (peak working set delta)

-- General information --

File name: example.mzML
File type: mzML

Instrument: LTQ Orbitrap XL
  Mass Analyzer: Orbitrap (resolution: 0)

MS levels: 1, 2
Total number of peaks: 479455
Number of spectra: 1684

Ranges:
  retention time: 1501.41 .. 2499.52 sec (16.6 min)
  mass-to-charge: 85.81 .. 799.95
  intensity: 0.67 .. 11977811.00

Number of spectra per MS level:
  level 1: 564
  level 2: 1120

Peak type from metadata (or estimated from data)
  level 1: Centroid (Centroid)
  level 2: Centroid (Centroid)

Activation methods
  MS-Level 2 & CID (Collision-induced dissociation): 1120

Precursor charge distribution:
  charge 2: 679x
  charge 3: 399x
  charge 4: 33x
  charge 5: 8x
  charge 6: 1x

FileInfo took 0.26 s (wall), 0.26 s (CPU), 0.01 s (system), 0.25 s (user); Peak Memory Usage: 59 MB.