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pyOpenMS Mass Spectrometry Workflows

Run end-to-end proteomics and metabolomics LC-MS/MS analysis with ready-made pyOpenMS CLI scripts.

Data & AnalyticsAdvanced★ 33,030⑂ 3,248AI score 9/10Last updated: Aug 9, 2026

What it does

  • Inspects and converts MS files (mzML/mzXML/MGF/featureXML/consensusXML/idXML) and runs configurable signal-processing chains.
  • Detects features for metabolomics (MassTraceDetection → ElutionPeakDetection → FeatureFindingMetabo) and peptides (FeatureFinderAlgorithmPicked), then aligns RT, links consensus features and exports quant matrices.
  • Handles annotation: adduct grouping, HMDB accurate-mass search, GNPS FBMN / SIRIUS export, plus FDR filtering of search results.
  • Provides chemistry helpers: monoisotopic/average mass, in-silico digestion, theoretical fragment spectra, chromatogram extraction and plots.
  • Documents pyOpenMS 3.5.0 breaking API changes so legacy tutorial code doesn't silently fail.

Who it's for

  • Proteomics/metabolomics researchers and core-facility analysts.
  • Python users automating OpenMS pipelines.
  • Anyone hitting errors from outdated OpenMS examples.

Examples

  1. python scripts/inspect_ms_data.py sample.mzML --spectra-csv spectra.csv for a quick raw-file audit.
  2. Multi-sample study: align_link_quantify.py s1.mzML s2.mzML s3.mzML --out-prefix study then consensus_to_matrix.py study.consensusXML --normalize median.
  3. Peptide chemistry: mass_calculator.py --peptide "PEPTIDEM(Oxidation)K" --charges 1 2 3 --isotopes 5.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/pyopenms/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/pyopenms folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/pyopenms/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git /tmp/sas && mkdir -p ~/.claude/skills && cp -r /tmp/sas/skills/pyopenms ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Confirm Python 3.9+ and uv are installed (python --version, uv --version).
  2. Clone the repo: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Copy the skill: mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/pyopenms ~/.claude/skills/
  4. Install the library: uv pip install pyopenms (targets 3.5.0).
  5. Verify: python -c "import pyopenms as ms; print(ms.__version__)" — the one-line memory notice on import is harmless.
  6. Restart Claude Code and ask something like "analyze this mzML file" to trigger the skill. For HMDB structure annotation, supply HMDB2StructMapping.tsv yourself.
View source on GitHub ↗License: MIT