HIGHLIGHTS
SUMMARY
Metabolomics refers to the comprehensive profiling of metabolite abundances, which are typically measured using mass spectrometry (MS) or nuclear magnetic_resonance (NMR) spectrometry. In practice, metabolomics data are known to contain a mixture of MAR, MCAR and MNAR missing data which are typically omitted from the data set for further analyses, or otherwise, they are imputed. A technique for omitting missing data is to assess whether multivariate data missing values are MCAR or not, before omitting the values. Subsequently, the authors use the trained model to predict the missing mechanism in the full data matrix . . .
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