Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 33169034.
- Also identified by DOI 10.1038/s41587-020-0700-3 and PMC identifier 7971188.
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Abstract
We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.
Medical subject headings
- Algorithms
- Gas Chromatography-Mass Spectrometry
- Metabolomics