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Enabling pan-repository reanalysis for big data science of public metabolomics data

Yasin El Abiead, Michael Strobel, Thomas Payne, Eoin Fahy, Claire O’Donovan, Shankar Subramamiam, Juan Antonio Vizcaíno, Özgür Yürekten, Victoria Deleray, Simone Zuffa, Shipei Xing, Helena Mannochio-Russo, Ipsita Mohanty, Haoqi Nina Zhao, Andrés Mauricio Caraballo‐Rodríguez, Paulo Wender Portal Gomes, Nicole E. Avalon, Trent R. Northen, Benjamin P. Bowen, Katherine Louie, Pieter C. Dorrestein, Mingxun Wang

2025Nature Communications32 citationsDOIOpen Access PDF

Abstract

Public untargeted metabolomics data is a growing resource for metabolite and phenotype discovery; however, accessing and utilizing these data across repositories pose significant challenges. Therefore, here we develop pan-repository universal identifiers and harmonized cross-repository metadata. This ecosystem facilitates discovery by integrating diverse data sources from public repositories including MetaboLights, Metabolomics Workbench, and GNPS/MassIVE. Our approach simplified data handling and unlocks previously inaccessible reanalysis workflows, fostering unmatched research opportunities.

Topics & Concepts

WorkflowMetadataWorkbenchData scienceComputer scienceMetabolomicsIdentifierData curationBig dataResource (disambiguation)Information repositoryElixir (programming language)World Wide WebData miningBioinformaticsDatabaseBiologyProgramming languageComputer data storageVisualizationComputer networkOperating systemMetabolomics and Mass Spectrometry StudiesBiomedical Text Mining and OntologiesScientific Computing and Data Management
Enabling pan-repository reanalysis for big data science of public metabolomics data | Litcius