Skills pyopenms
🔬

pyopenms

Safe ⚡ Contains scripts🌐 Network access📁 Filesystem access🔑 Env variables⚙️ External commands

Analyze mass spectrometry data

Also available from: davila7

Process proteomics and metabolomics data with comprehensive mass spectrometry tools. This skill provides access to OpenMS algorithms for file format handling, spectral processing, feature detection, and peptide identification workflows.

Supports: Claude Codex Code(CC)
🥉 72 Bronze
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Test it

Using "pyopenms". Load an mzML file and show me the first spectrum

Expected outcome:

  • Use MSExperiment to hold the data and MzMLFile to load it
  • Access spectra via iteration or getSpectrum(index) method
  • Extract m/z and intensity values with get_peaks() which returns numpy arrays
  • Get metadata like MS level and retention time with getMSLevel() and getRT()

Using "pyopenms". How do I apply signal processing to my spectra?

Expected outcome:

  • Use GaussFilter or SavitzkyGolayFilter for smoothing
  • Set parameters with getParameters() and setValue()
  • Apply with filterExperiment() method
  • Consider normalization with LinearNormalizer before processing

Security Audit

Safe
v4 • 1/17/2026

This skill contains only markdown documentation files with Python code examples. The static analyzer incorrectly flagged markdown syntax patterns as security threats. All 295 static findings are false positives. No executable code exists in this skill.

8
Files scanned
4,192
Lines analyzed
5
findings
4
Total audits

Risk Factors

⚡ Contains scripts
No specific locations recorded
🌐 Network access (1)
SKILL.md:203-205
📁 Filesystem access
No specific locations recorded
🔑 Env variables
No specific locations recorded
⚙️ External commands (7)
SKILL.md:19-214 references/data_structures.md:13-497 references/feature_detection.md:22-410 references/file_io.md:39-349 references/identification.md:23-422 references/metabolomics.md:11-482 references/signal_processing.md:11-433
Audited by: claude View Audit History →

Quality Score

45
Architecture
100
Maintainability
85
Content
29
Community
100
Security
91
Spec Compliance

What You Can Build

Quantitative proteomics

Process LC-MS/MS datasets to identify and quantify proteins across multiple samples

Pipeline development

Build automated mass spectrometry data processing pipelines with Python

Metabolite analysis

Perform untargeted metabolomics preprocessing and feature annotation

Try These Prompts

Basic file loading 
How do I load an mzML file and access the spectra and chromatograms using pyopenms?
Feature detection 
Show me how to detect features in centroided mass spectrometry data using the FeatureFinder in pyopenms.
Peptide identification 
How do I load identification results from an idXML file and apply false discovery rate filtering in pyopenms?
Advanced workflows 
Create a complete pyopenms workflow that loads mzML data, processes spectra, detects features, and exports results to a pandas DataFrame.

Best Practices

  • Use IndexedMzMLFileLoader for large files to avoid loading entire dataset into memory
  • Apply appropriate signal processing (smoothing, filtering) before feature detection
  • Validate file existence with os.path.exists() before loading data

Avoid

  • Loading very large mzML files entirely into memory without using streaming or indexed access
  • Skipping quality control steps before downstream analysis
  • Ignoring instrument metadata that may affect data interpretation

Frequently Asked Questions

What file formats does pyopenms support?
mzML, mzXML, mzData, idXML, mzIdentML, pepXML, protXML, featureXML, consensusXML, mzTab, FASTA, and TraML.
How do I install pyopenms?
Use uv: uv pip install pyopenms. Requires Python 3.8+ and has C++ dependency requirements.
Can pyopenms run without OpenMS installed?
No, pyopenms is a Python wrapper around the OpenMS C++ library which must be available on the system.
Does pyopenms include search engines?
No, pyopenms integrates with search engines but you must install them separately (Comet, Mascot, MSGFPlus, etc.).
How do I export data to pandas?
Use the get_df() method on FeatureMap, ConsensusMap, or other data containers to export directly to DataFrames.
What is the difference between pyopenms and matchms?
pyopenms is comprehensive for proteomics workflows. Use matchms for simple spectral comparison and metabolite identification.

Developer Details

Author

K-Dense-AI

License

3 clause BSD license

Repository

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/pyopenms

Ref

main

File structure

📁 references/

📄 data_structures.md

📄 feature_detection.md

📄 file_io.md

📄 identification.md

📄 metabolomics.md

📄 signal_processing.md

📄 SKILL.md