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Enabling pan-repository reanalysis for big data science of public metabolomics data
- El Abiead, Yasin;
- Strobel, Michael;
- Payne, Thomas;
- Fahy, Eoin;
- O’Donovan, Claire;
- Subramamiam, Shankar;
- Vizcaíno, Juan Antonio;
- Yurekten, Ozgur;
- Deleray, Victoria;
- Zuffa, Simone;
- Xing, Shipei;
- Mannochio-Russo, Helena;
- Mohanty, Ipsita;
- Zhao, Haoqi Nina;
- Caraballo-Rodriguez, Andres M;
- P. Gomes, Paulo Wender;
- Avalon, Nicole E;
- Northen, Trent R;
- Bowen, Benjamin P;
- Louie, Katherine B;
- Dorrestein, Pieter C;
- Wang, Mingxun
Published Web Location
https://doi.org/10.1038/s41467-025-60067-yAbstract
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.
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