Using Out-of-Batch Reference Populations to Improve Untargeted Metabolomics for Screening Inborn Errors of Metabolism

Using Out-of-Batch Reference Populations to Improve Untargeted Metabolomics for Screening Inborn Errors of Metabolism

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to ju...

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Bibliographic Details
Main Authors: Michiel Bongaerts, Ramon Bonte, Serwet Demirdas, Edwin H. Jacobs, Esmee Oussoren, Ans T. van der Ploeg, Margreet A. E. M. Wagenmakers, Robert M. W. Hofstra, Henk J. Blom, Marcel J. T. Reinders, George J. G. Ruijter
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Metabolites
Subjects:
untargeted metabolomics
inborn errors of metabolism
normalization
internal standards
batch effects
Online Access:https://www.mdpi.com/2218-1989/11/1/8

Internet

https://www.mdpi.com/2218-1989/11/1/8

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