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, Ozgur Yurekten, Victoria Deleray, Simone Zuffa, Shipei Xing, Helena Mannochio-Russo, Ipsita Mohanty, Haoqi Nina Zhao, Andres M. Caraballo-Rodriguez, Paulo Wender P. Gomes, Nicole E. Avalon, Trent R. Northen, Benjamin P. Bowen, Katherine B. Louie, Pieter C. Dorrestein and Mingxun Wang ()
Additional contact information
Yasin El Abiead: University of California San Diego
Michael Strobel: University of California Riverside
Thomas Payne: Wellcome Genome Campus, Hinxton
Eoin Fahy: University of California, San Diego
Claire O’Donovan: Wellcome Genome Campus, Hinxton
Shankar Subramamiam: University of California, San Diego
Juan Antonio Vizcaíno: Wellcome Genome Campus, Hinxton
Ozgur Yurekten: Wellcome Genome Campus, Hinxton
Victoria Deleray: University of California San Diego
Simone Zuffa: University of California San Diego
Shipei Xing: University of California San Diego
Helena Mannochio-Russo: University of California San Diego
Ipsita Mohanty: University of California San Diego
Haoqi Nina Zhao: University of California San Diego
Andres M. Caraballo-Rodriguez: University of California San Diego
Paulo Wender P. Gomes: University of California San Diego
Nicole E. Avalon: University of California San Diego
Trent R. Northen: Lawrence Berkeley National Lab
Benjamin P. Bowen: Lawrence Berkeley National Lab
Katherine B. Louie: Lawrence Berkeley National Laboratory
Pieter C. Dorrestein: University of California San Diego
Mingxun Wang: University of California Riverside

Nature Communications, 2025, vol. 16, issue 1, 1-7

Abstract: 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.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-60067-y

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DOI: 10.1038/s41467-025-60067-y

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