Illustration of MINT analysis in mixOmics.

A: Parameter tuning of a MINT sPLS-DA model with two components using Leave-One-Group-Out cross-validation and maximum distance, BER (y-axis) with respect to number of selected features (x-axis). Full diamond represents the optimal number of features to select on each component, B: Performance of the final MINT sPLS-DA model including selected features based on BER and classification error rate per class, C: Global sample plot with confidence ellipse plots, D: Study specific sample plot, E: Clustered Image Map (Euclidean Distance, Complete linkage). Samples are represented in rows, selected features on the first component in columns. F: Loading plot of each feature selected on the first component in each study, with color indicating the class with a maximal mean expression value for each gene.