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MetaboSERV-a platform for selecting, exchanging, and visualizing metabolomics data with controlled data access.
GigaScience 14:giaf075 (2025)
BACKGROUND: The growing number of metabolomics studies, based on high-dimensional data measured by hyphenated mass spectrometry (MS) and/or nuclear magnetic resonance (NMR) spectroscopy, has sparked the creation of several public metabolomics data repositories. Each repository emphasizes different aspects regarding data selection and representation, but most offer only limited options for privacy-preserving data sharing. RESULTS: We present MetaboSERV, an open-source, browser-based metabolomics platform dedicated to the selection, integration, and sharing of quantitative metabolomics data and metadata with controlled data access. MetaboSERV aims to aid researchers in analyzing their results by facilitating means to browse, visualize, and compare data across available datasets. It provides different access control functionalities, creating an environment in which data can be shared safely in a privacy-preserving manner to support collaborative and interdisciplinary research. Furthermore, it is designed to be extensible and adaptable to existing data management infrastructures through the creation of self-managed MetaboSERV instances, for which we provide the source code and a set of configurable Docker images. CONCLUSIONS: The public MetaboSERV instance is available at https://metaboserv.ckdn.app, and the source code can be found at https://gitlab.gwdg.de/MedBioinf/metabolomics/metaboserv. The Research Resource Identifier (RRID) for MetaboSERV is SCR_025496.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
(privacy-preserving) Data Sharing ; Collaborative Research ; Mass Spectrometry ; Metabolomics ; Nuclear Magnetic Resonance Spectroscopy; Acute Kidney Injury; Repository; Metabolights; Discovery; Urine
e-ISSN
2047-217X
Journal
GigaScience
Quellenangaben
Volume: 14,
Article Number: giaf075
Publisher
Oxford Univ Press
Publishing Place
London
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)
Grants
German Federal Ministry of Education and Research (BMBF)