Principal Component Analysis (Principal Component Analysis, PCA) is the linear recombination of all metabolites originally identified, forming a set of new comprehensive variables, and selecting 2-3 comprehensive variables from them based on the analyzed problem, to reflect as much information of the original variables as possible, thus achieving the purpose of dimension reduction. At the same time, PCA of metabolites can also reflect the variability between and within groups overall.
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