Improved One-Class Modeling of High-Dimensional Metabolomics Data via Eigenvalue-Shrinkage

Improved One-Class Modeling of High-Dimensional Metabolomics Data via Eigenvalue-Shrinkage

One-class modelling is a useful approach in metabolomics for the untargeted detection of abnormal metabolite profiles, when information from a set of reference observations is available to model “normal” or baseline metabolite profiles. Such outlying profiles are typically identified by comparing th...

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Bibliographic Details
Main Authors: Alberto Brini, Vahe Avagyan, Ric C. H. de Vos, Jack H. Vossen, Edwin R. van den Heuvel, Jasper Engel
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Metabolites
Subjects:
high-dimensional data
one-class model
untargeted metabolomics
mahalonobis distance
eigenvalue-shrinkage
critical value
Online Access:https://www.mdpi.com/2218-1989/11/4/237

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https://www.mdpi.com/2218-1989/11/4/237

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