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pyopenms

Provide Python bindings to the OpenMS mass spectrometry library for proteomics and metabolomics data processing.

22|4|Updated May 25, 2026
Search Tags:#metabolomics#data-analysis#mass-spectrometry#proteomics#pyopenms#openms#python-bindings
One-click install
npx skills add https://github.com/crazymsn/academic-skills --skill pyopenms-crazymsn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pyopenms
Source: https://github.com/crazymsn/academic-skills/tree/main/academic-skills/pyopenms
Command: npx skills add https://github.com/crazymsn/academic-skills --skill pyopenms-crazymsn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Bridge the OpenMS C++ mass spectrometry library to Python, enabling researchers to access powerful proteomics and metabolomics data processing workflows directly from Python without rebuilding native code.

Core Features & Use Cases

  • Python bindings to OpenMS data structures (MSExperiment, MSSpectrum, FeatureMap) for scripting, analysis, and rapid prototyping.
  • End-to-end workflows: file I/O, spectral processing, feature detection, identification, and downstream analytics in Python.
  • Real-world use: load mzML data, perform peak picking, run feature finding, and map identifications within a single script or notebook.

Quick Start

Install the pyopenms package and begin by loading a mzML file into an MSExperiment to prototype a proteomics workflow.

Frequently Asked Questions about pyopenms

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I process mass spectrometry data in Python for proteomics workflows?▼

You can process mass spectrometry data in Python using pyopenms, which provides Python bindings to the OpenMS C++ library for file I/O, signal processing, feature detection, and peptide identification across LC-MS datasets.

Can I load mzML files and run feature detection in a single Python script?▼

Yes, you can load mzML files into an MSExperiment object and run feature finding within a single script or notebook using pyopenms to prototype end-to-end proteomics and metabolomics workflows.

Do I need to compile the OpenMS C++ core to use these Python bindings?▼

No, you do not need to rebuild native code. The pyopenms package requires the OpenMS C++ core compiled for Python and exposes core data structures and workflows directly via the pyopenms API.

What data structures are available for scripting LC-MS data analysis?▼

pyopenms exposes OpenMS data structures like MSExperiment, MSSpectrum, and FeatureMap for scripting, analysis, and rapid prototyping of mass spectrometry workflows in Python.

Does pyopenms support metabolomics data processing as well as proteomics?▼

Yes, pyopenms supports both proteomics and metabolomics data processing, enabling researchers to access spectral processing, peak picking, and downstream analytics across mass spectrometry datasets.

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