Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) is a discriminant analysis method in multivariate data analysis techniques, often used to deal with classification and discrimination problems. By appropriately rotating the principal components, OPLS can effectively distinguish between group observations and identify the influential variables that cause differences between groups.

Input

group.txt

otu.txt

Output

In the graph, the horizontal axis represents the predictive principal components, so the differences between groups can be observed along the horizontal direction; the vertical axis represents the orthogonal principal components, so the differences within groups can be observed along the vertical direction. Each point in the graph represents a sample, and samples from the same group are indicated by the same color.