Pyopenms

This is the Python interface to OpenMS, the computational mass spectrometry library that proteomics and metabolomics researchers actually use. It handles the full pipeline: reading mzML/mzXML files, signal processing, feature detection across LC-MS runs, and peptide identification workflows. The API wraps C++ underneath, so you get decent performance while staying in Python. Especially useful if you're dealing with quantitative proteomics where you need to align features across multiple samples or integrate results from search engines like Comet or Mascot. The parameter system takes some getting used to, but once you're past that, it beats writing custom parsers for every mass spec file format.

skills.sh installs: 219
GitHub stars: 33.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add davila7/claude-code-templates --skill pyopenms --agent claude-code

Installs into .claude/skills of the current project.

Files

PyOpenMS

Overview

PyOpenMS provides Python bindings to the OpenMS library for computational mass spectrometry, enabling analysis of proteomics and metabolomics data. Use for handling mass spectrometry file formats, processing spectral data, detecting features, identifying peptides/proteins, and performing quantitative analysis.

Installation

Install using uv:

uv uv pip install pyopenms

Verify installation:

import pyopenms
print(pyopenms.__version__)

Core Capabilities

PyOpenMS organizes functionality into these domains:

1. File I/O and Data Formats

Handle mass spectrometry file formats and convert between representations.

Supported formats: mzML, mzXML, TraML, mzTab, FASTA, pepXML, protXML, mzIdentML, featureXML, consensusXML, idXML

Basic file reading:

import pyopenms as ms

# Read mzML file
exp = ms.MSExperiment()
ms.MzMLFile().load("data.mzML", exp)

# Access spectra
for spectrum in exp:
    mz, intensity = spectrum.get_peaks()
    print(f"Spectrum: {len(mz)} peaks")

For detailed file handling: See references/file_io.md