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Updated: Sep 5, 2025

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
Published on: September 20, 2022
Enhancing untargeted metabolomics using metadata-based source annotation
Julia M Gauglitz1,2, Kiana A West1,2, Wout Bittremieux1,2
1Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, USA.
Abstract:
Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.
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