What Are PLS-DA/OPLS-DA 2D Plots Used For?
PLS-DA (Partial Least Squares Discriminant Analysis) and OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) are widely employed multivariate statistical methods, particularly in high-throughput biomedical research areas such as metabolomics and proteomics. These approaches enable the reduction of high-dimensional data into two- or three-dimensional representations, facilitating the visualization of inter-sample variation. PLS-DA is grounded in partial least squares regression and is primarily used to investigate the relationship between continuous response variables and multiple predictors—for instance, linking metabolite profiles of biological specimens to phenotypic traits such as disease states. OPLS-DA extends PLS-DA by introducing orthogonal components that separate predictive variation from orthogonal (non-predictive) variation, allowing for more precise sample classification and feature selection.
Both PLS-DA and OPLS-DA aid in identifying variables associated with group separation, uncovering latent biological patterns, and supporting biomarker discovery, thereby contributing to advances in disease diagnosis and therapeutic research. As such, PLS-DA and OPLS-DA 2D plots possess significant analytical value in the context of biomedical data interpretation.
MtoZ Biolabs, an integrated chromatography and mass spectrometry (MS) services provider.
Related Services
How to order?
