Matchms — Spectral Matching & Metabolite Identification

Overview

Matchms is a Python library for mass spectrometry data processing focused on spectral similarity calculation and compound identification. It provides multi-format I/O, 50+ spectrum filters for metadata harmonization and peak processing, 8 similarity scoring functions, and a pipeline framework for reproducible analytical workflows.

When to Use

• Identifying unknown metabolites by matching MS/MS spectra against reference libraries
• Computing spectral similarity scores (cosine, modified cosine, fingerprint-based)
• Processing and standardizing mass spectral data from multiple formats (mzML, MGF, MSP, JSON)
• Building reproducible spectral processing pipelines for quality control
• Harmonizing metadata across spectral databases (compound names, SMILES, InChI, adducts)
• Large-scale spectral library comparisons and duplicate detection
• For full LC-MS/MS proteomics workflows (feature detection, protein ID), use pyopenms instead
• For chemical structure similarity without mass spectra, use rdkit fingerprint comparison

Prerequisites