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Critical assessment of chromatographic metadata in publicly available metabolomics data repositories.
Metabolomics 18:97 (2022)
Publ. Version/Full Text
Research data
DOI
PMC
Introduction: The structural identification of metabolites represents one of the current bottlenecks in non-targeted liquid chromatography-mass spectrometry (LC–MS) based metabolomics. The Metabolomics Standard Initiative has developed a multilevel system to report confidence in metabolite identification, which involves the use of MS, MS/MS and orthogonal data. Limitations due to similar or same fragmentation pattern (e.g. isomeric compounds) can be overcome by the additional orthogonal information of the retention time (RT), since it is a system property that is different for each chromatographic setup. Objectives: In contrast to MS data, sharing of RT data is not as widespread. The quality of data and its (re-)useability depend very much on the quality of the metadata. We aimed to evaluate the coverage and quality of this metadata from public metabolomics repositories. Methods: We acquired an overview on the current reporting of chromatographic separation conditions. For this purpose, we defined the following information as important details that have to be provided: column name and dimension, flow rate, temperature, composition of eluents and gradient. Results: We found that 70% of descriptions of the chromatographic setups are incomplete (according to our definition) and an additional 10% of the descriptions contained ambiguous and/or incorrect information. Accordingly, only about 20% of the descriptions allow further (re-)use of the data, e.g. for RT prediction. Therefore, we have started to develop a unified and standardized notation for chromatographic metadata with detailed and specific description of eluents, columns and gradients. Conclusion: Reporting of chromatographic metadata is currently not unified. Our recommended suggestions for metadata reporting will enable more standardization and automatization in future reporting.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Data Reuse ; Lc-ms ; Metabolomics ; Repositories ; Retention Time
ISSN (print) / ISBN
1573-3882
e-ISSN
1573-3890
Journal
Metabolomics
Quellenangaben
Volume: 18,
Issue: 12,
Article Number: 97
Publisher
Springer
Publishing Place
New York, NY
Non-patent literature
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Reviewing status
Peer reviewed
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Deutsche Forschungsgemeinschaft