Journal
NATURE METHODS
Volume 14, Issue 1, Pages 57-60Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.4072
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Funding
- European Union [634402, 305259]
- Russian Government Program of Competitive Growth of Kazan Federal University
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High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target decoy FDR estimate for spatial metabolomics.
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