A Workflow for Missing Values Imputation of Untargeted Metabolomics Data

Metabolomics studies have seen a steady growth due to the development and implementation of affordable and high-quality metabolomics platforms. In large metabolite panels, measurement values are frequently missing and, if neglected or sub-optimally imputed, can cause biased study results. We provide...

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Autors principals:	Tariq Faquih, Maarten van Smeden, Jiao Luo, Saskia le Cessie, Gabi Kastenmüller, Jan Krumsiek, Raymond Noordam, Diana van Heemst, Frits R. Rosendaal, Astrid van Hylckama Vlieg, Ko Willems van Dijk, Dennis O. Mook-Kanamori
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2020-11-01
Col·lecció:	Metabolites
Matèries:	imputation multiple imputation using chained equations k-nearest neighbors untargeted metabolomics metabolon simulation
Accés en línia:	https://www.mdpi.com/2218-1989/10/12/486
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