 On the other hand, multivariate statistics are thriving methods for high-dimensional correlated metabolomics data, of which the most popular one is Projection to Latent Structures (PLS) regression and its classification version PLS-DA.Other data mining methods, such as random forest, support-vector machines, etc.are received increasing attention for untargeted metabolomics data analysis.