OPLS-DA Service

Orthogonal partial least squares discriminant analysis (OPLS-DA) was introduced as an improvement of the PLS-DA approach to discriminate two or more groups (classes) using multivariate data. In OPLS-DA, a regression model is constructed between the multivariate data and a response variable that only contains class information. The obvious advantage of OPLS-DA compared with PLS-DA is that a single component serves as a predictor for the class, while the other components describe the variation orthogonal to the first predictive component.