matchms

Compare mass spectra from MGF, mzML, and MSP files using cosine similarity.

Updated Mar 10, 2026

Search Tags:#data analysis #metabolomics #mass spectrometry #proteomics #compound identification #spectral similarity

Ready to run

npx skills add https://github.com/felixboehm/biochem-allergy --skill matchms-felixboehm

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: matchms
Source: https://github.com/felixboehm/biochem-allergy/tree/main/.claude/skills/matchms
Command: npx skills add https://github.com/felixboehm/biochem-allergy --skill matchms-felixboehm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matchms, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies the complex process of analyzing mass spectrometry data, enabling faster and more accurate compound identification and comparison.

Core Features & Use Cases

Spectral Similarity: Compare mass spectra using various algorithms (cosine, modified cosine) to find matches in libraries.
Compound Identification: Identify unknown compounds by matching their spectra against known spectral libraries.
Data Processing: Import, filter, and standardize mass spectrometry data from various formats (MGF, mzML, MSP).
Use Case: A researcher has a list of unknown compounds detected in a metabolomics experiment. They can use this Skill to compare these unknown spectra against a large spectral library to identify potential metabolites.

Quick Start

Use the matchms skill to compare spectra in 'unknowns.mgf' against 'library.mgf' using cosine similarity.

Frequently Asked Questions about matchms

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I calculate spectral similarity for mass spectrometry data?▼

Spectral similarity is calculated by comparing mass spectra using algorithms like cosine or modified cosine to find matches in spectral libraries. This skill requires the matchms library to import, filter, and score spectra from formats like MGF, mzML, and MSP.

How do I identify unknown compounds from metabolomics mass spectrometry data?▼

Compound identification matches unknown spectra against known spectral libraries. You can import your experimental data in formats like MGF or MSP, filter the spectra, and compare them to identify potential metabolites.

Can I import and filter mass spectrometry data from MGF and mzML files?▼

Yes, you can import, filter, and standardize mass spectrometry data from MGF, mzML, and MSP formats. The skill uses the matchms library to preprocess spectra before performing similarity scoring or compound identification.

What is the best way to compare unknown mass spectra against a spectral library?▼

The best way to compare unknown mass spectra against a library is by using cosine similarity algorithms. This skill facilitates direct comparison of unknown spectra against large reference libraries to identify matching compounds.

Does matchms support both metabolomics and proteomics mass spectrometry analysis?▼

Yes, matchms supports mass spectrometry data analysis for both metabolomics and proteomics research. It enables spectral similarity calculations, compound identification from libraries, and data preprocessing across both scientific domains.

What mass spectrometry data formats are supported for compound identification?▼

Supported mass spectrometry data formats include MGF, mzML, and MSP. The skill imports spectra from these formats to perform filtering, standardization, and subsequent compound identification using spectral library matching.