Univariate analysis is very common in statistical analysis, with only one variable involved. The analytic results are descriptive or inferential, thus this analysis is widely used for the analysis of data collected from proteomics or metabolomics. Metabolomic data are usually multi-dimensional, with the number of features (peaks, metabolites) ranging from several dozen to hundreds or even thousands.