pyopenms
Complete mass spectrometry analysis platform. Use for proteomics and metabolomics workflows—feature detection, peptide/protein identification, label-free and isobaric quantification, adduct/accurate-mass annotation, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. For simple spectral comparison and small-molecule library matching use matchms.
npx skills add K-Dense-AI/scientific-agent-skills --skill pyopenms --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# PyOpenMS ## Overview PyOpenMS provides Python bindings to the OpenMS library for computational mass spectrometry, enabling analysis of proteomics and metabolomics data. Use it to read/write MS file formats, process raw spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines. **This skill ships ready-to-run scripts in `scripts/`** covering the most common high-level workflows. Prefer running a script over writing new code—each is a parameterized CLI tool that handles loading, processing, and export. Drop into the Python API (and the `references/`) only when no script fits. ## Installation ```bash uv pip install pyopenms ``` Verify (note: `__version__` works, but the bundled binary prints a one-line memory-status notice on import that is harmless): ```python import pyopenms as ms print(ms.__version__) # 3.5.0 ``` ## Scripts (start here) Run with `python scripts/<name>.py --help` for full options. All accept standard MS file formats and write featureXML/consensusXML/CSV/mzTab/PNG as appropriate. ### Inspect & convert | Script | What it does | |--------|--------------| | `inspect_ms_data.py` | Summarize any mzML/mzXML/featureXML/co
- Overview
- Installation
- Scripts (start here)
- Inspect & convert
- Feature detection & quantification
- Annotation
- Identification
- Chemistry
- Targeted & visualization
- Common script recipes
- Key 3.5.0 API notes
- Core data structures
- Parameter management
- Export to pandas
uv pip install pyopenms Inspect a file python scripts/inspect_ms_data.py sample.mzML --spectra-csv spectra.csv Untargeted metabolomics: features for one sample python scripts/detect_features_metabo.py sample.mzML --out-csv features.csv Full multi-sample quantification study python scripts/align_link_quantify.py s1.mzML s2.mzML s3.mzML --out-prefix study python scripts/consensus_to_matrix.py study.consensusXML --out quant.csv --normalize median Peptide chemistry python scripts/mass_calculator.py --peptide "PEPTIDEM(Oxidation)K" --charges 1 2 3 --isotopes 5
What does the pyopenms skill do?
Complete mass spectrometry analysis platform. Use for proteomics and metabolomics workflows—feature detection, peptide/protein identification, label-free and isobaric quantification, adduct/accurate-mass annotation, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. For simple spectral comparison and small-molecule library matching use matchms.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill pyopenms --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.