Import mass spectrometry spectra from mzML, mgf, MSP, and GNPS JSON formats.
npx skills add https://github.com/rubensliv/k-dense-ai --skill matchms-rubensliv
Please help me install this Agent Skill. Skill: matchms Source: https://github.com/rubensliv/k-dense-ai/tree/main/scientific-skills/matchms Command: npx skills add https://github.com/rubensliv/k-dense-ai --skill matchms-rubensliv
Mass spectrometry data analysis requires robust tooling to import, harmonize metadata, compare samples, and identify compounds across large libraries.
Load spectra from supported formats (mzML, mgf, MSP, JSON) and run CosineGreedy to identify top matches against a reference library.
High-intent search queries and answers about installing and using this skill.
To compute cosine similarity for mass spectrometry data, load spectra from mzML, mgf, MSP, or GNPS JSON formats and apply metrics like CosineGreedy, CosineHungarian, or ModifiedCosine to identify top matches against a reference library.
Spectral library matching compares query spectra against references using similarity metrics. Metadata harmonization standardizes cross-platform mass spectrometry data imports to ensure reproducible compound identification workflows.
Yes, you can run large-scale library searches on mzML and MSP files. The system supports scalable pipelines for spectral matching, metadata enrichment, and cross-platform data exchange across mass spectrometry datasets.
Yes, it supports NeutralLossesCosine and other pluggable similarity functions. The modular design allows optional components directories for scripts and references, enabling custom similarity functions and reproducible workflows.
The best way to standardize spectra from GNPS JSON is using the built-in import and filtering capabilities. This harmonizes metadata and enables cross-platform data exchange for downstream mass spectrometry analysis.
Use ModifiedCosine instead of CosineGreedy when comparing spectra with expected chemical modifications. Both are available similarity metrics, alongside CosineHungarian, to drive reproducible workflows depending on your specific compound matching needs.
felixboehmCompare mass spectra from MGF, mzML, and MSP files using cosine similarity.
jasrajtulsiProcess mass spectrometry spectra for similarity scoring and compound identification.
jaechang-hitsMatch unknown MS/MS spectra against spectral libraries using matchms similarity scoring.
jackspaceProcess MS/MS spectra with filtering, similarity scoring, and metadata harmonization pipelines.
