Agent skill · research science · k-dense-ai
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.
Why this skill is useful
Includes ready-to-run scripts for complex mass spectrometry workflows that automate data processing and analysis.
What it needs
Requires python, uv installed locally. About 4k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.
What this skill does
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 Verify (note: version works, but the bundled binary prints a one-line memory-status notice on import that is harmless): 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 -------- -------------- inspectmsdata.py Summarize any mzML/mzXML/featureXML/consensusXML/idXML (counts, RT/m/z ranges, TIC, metadata); optional per-spectrum CSV. convertformat.py Convert between mzML/mzXML/MGF with optional MS-level, RT, and intensity filtering. processspectra.py Configurable signal-processing chain: smoothing (Gauss/SGolay), centroiding (PeakPickerHiRes), normalization, S/N and intensity thresholds. Feature detection & quantification Script What it does -------- -------------- detectfeaturesmetabo.py Untargeted metabolomics feature finding: MassTraceDetection → ElutionPeakDetection → FeatureFindingMetabo. detectfeaturescentroided.py Peptide/centroided feature detection via FeatureFinderAlgorithmPicked. alignlinkquantify.py Multi-sample pipeline: detect (or load) features → RT alignment → consensus linking → quant matrix CSV. consensustomatrix.py consensusXML → wide intensity matrix + metadata, with optional median/quantile normalization and long format. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills k-dense-ai/pyopenms