Human untargeted metabolomics studies succeed in annotating only ~10% of molecular features. We, therefore, introduce reference data-driven analysis that uses the source data as a pseudo-MS/MS reference library to match against human metabolomics MS/MS data. We demonstrate this approach with food source data, allowing an empirical assessment of dietary patterns from untargeted data but is broadly applicable and provides an additional layer of interpretability to metabolomics data.
This repository contains code to generate the figures associated with the following manuscript:
- Gauglitz et al. Reference data-set driven metabolomics. Research Square (2021). doi:10.21203/rs.3.rs-654519/v1
For more information, please contact Pieter Dorrestein.