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matchms

Calculate spectral similarity between query spectra and reference libraries.

2|Updated Jun 4, 2026
Search Tags:#bioinformatics#metabolomics#mass spectrometry#data processing#chemistry#spectral analysis
One-click install
npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill matchms-lord1egypt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: matchms
Source: https://github.com/Lord1Egypt/scientific-agent-toolkit/tree/main/scientific-skills/matchms
Command: npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill matchms-lord1egypt

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill addresses the complexity of mass spectrometry data analysis by providing a standardized, reproducible framework for processing, filtering, and comparing spectral data against reference libraries.

Core Features & Use Cases

  • Spectral Preprocessing: Harmonize metadata, normalize intensities, and filter noise from raw mass spectrometry data.
  • Similarity Scoring: Calculate spectral similarity using various metrics like CosineGreedy, ModifiedCosine, and NeutralLossesCosine.
  • Workflow Automation: Build robust, multi-step pipelines for large-scale library searching and compound identification.

Quick Start

Use the matchms skill to load a mass spectrometry file and calculate the cosine similarity between the query spectra and a reference library.

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?▼

You can calculate spectral similarity by loading mass spectrometry files and applying scoring algorithms like CosineGreedy, ModifiedCosine, or NeutralLossesCosine to compare query spectra against a reference library.

What mass spectrometry file formats can I process for metabolomics?▼

You can process MGF, mzML, and MSP mass spectrometry file formats. The tool harmonizes metadata, normalizes intensities, and filters noise to prepare data for compound identification workflows.

How do I preprocess raw mass spectrometry data for compound identification?▼

To preprocess raw mass spectrometry data for compound identification, you harmonize metadata, normalize intensities, and filter noise. This establishes a standardized, reproducible framework for downstream library searching.

Can I build automated pipelines for large-scale spectral library searching?▼

Yes, you can build robust, multi-step pipelines for large-scale library searching and compound identification. This automates repetitive spectral matching tasks to ensure high-quality, reproducible analytical results.

Why do I need metadata harmonization for mass spectrometry analysis?▼

Metadata harmonization is needed for mass spectrometry analysis to standardize disparate data formats and ensure high-quality, reproducible analytical results when comparing spectra against reference libraries.

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