Chemometrics in Metabonomics

We provide an overview of how the underlying philosophy of chemometrics is integrated throughout metabonomic studies. Four steps are demonstrated: (1) definition of the aim, (2) selection of objects, (3) sample preparation and characterization, and (4) evaluation of the collected data. This includes the tools applied for linear modeling, for example, Statistical Experimental Design (SED), Principal Component Analysis (PCA), Partial least-squares (PLS), Orthogonal-PLS (OPLS), and dynamic extensions thereof. This is illustrated by examples from the literature. Keywords: Statistical Experimental Design (SED) • PCA • OPLS • Class-specific studies • Dynamic studies • Multivariate Design