Does Matchms support molecular structure analysis?

Yes, by installing the chemistry dependencies, you can derive InChI and SMILES, repair structural mismatches, and calculate molecular fingerprint similarities.

What file formats does Matchms support?

Matchms supports a wide range of formats including mzML, mzXML, MGF, MSP, GNPS-compatible JSON, and metabolomics-USI references.

Can I calculate modified cosine similarity with this skill?

Yes, Matchms includes specialized algorithms for Modified Cosine, CosineGreedy, and NeutralLossesCosine to account for precursor mass differences.

How does Matchms handle metadata harmonization?

It provides a comprehensive set of metadata filters that automatically standardize compound names, adducts, and charges into a consistent format.

Matchms Mass Spectrometry Analysis

Name: Matchms Mass Spectrometry Analysis
Author: Zehong-Wang

byZehong-Wang

0•

数据科学与机器学习

Processes and analyzes mass spectrometry data through spectral similarity, metadata harmonization, and automated workflows.

Matchms is a specialized Claude Code skill designed for scientists and researchers working with metabolomics and mass spectrometry data. It facilitates the end-to-end processing of spectral data, including importing from standard formats like mzML, MGF, and MSP, standardizing metadata, and applying advanced peak filters. The skill excels at calculating spectral similarities using metrics like Modified Cosine and NeutralLossesCosine, making it an essential tool for building reproducible analytical pipelines and identifying unknown compounds against reference libraries directly within your development environment.

主要功能

01Chemical annotation tools for deriving InChI, SMILES, and molecular fingerprints

02Advanced similarity metrics including CosineGreedy, ModifiedCosine, and FingerprintSimilarity

03Over 40 built-in filters for metadata harmonization and peak intensity processing

04Automated SpectrumProcessor for building reproducible multi-step analysis pipelines

05Support for multiple mass spectrometry formats including mzML, MGF, MSP, and JSON

060 GitHub stars

使用场景

01Standardizing and cleaning metabolomics datasets for high-throughput downstream analysis

02Developing automated quality control pipelines for raw mass spectrometry data

03Matching experimental unknown spectra against large-scale reference spectral libraries

主要功能

01Chemical annotation tools for deriving InChI, SMILES, and molecular fingerprints

02Advanced similarity metrics including CosineGreedy, ModifiedCosine, and FingerprintSimilarity

03Over 40 built-in filters for metadata harmonization and peak intensity processing

04Automated SpectrumProcessor for building reproducible multi-step analysis pipelines

05Support for multiple mass spectrometry formats including mzML, MGF, MSP, and JSON

060 GitHub stars

使用场景

01Standardizing and cleaning metabolomics datasets for high-throughput downstream analysis

02Developing automated quality control pipelines for raw mass spectrometry data

03Matching experimental unknown spectra against large-scale reference spectral libraries