Influence of missing values substitutes on multivariate analysis of metabolomics data
(2014)
Journal Article
Missing values are known to be problematic for the analysis of gas chromatography-mass spectrometry (GC-MS) metabolomics data. Typically these values cover about 10%–20% of all data and can originate from various backgrounds, including analytical, co... Read More about Influence of missing values substitutes on multivariate analysis of metabolomics data.