| Performs N-integration and feature selection with Projection to Latent Structures models (PLS) with sparse Discriminant Analysis |
| Name | Description | Version | Minimum Galaxy Version |
|---|---|---|---|
| performs N-integration and feature selection with Projection to Latent Structures models (PLS) with sparse Discriminant Analysis | 0.4.0 | 16.04 | |
| provides scatter plots for individuals (experimental units) representation in (sparse)(I)PCA,(regularized)CCA, (sparse)PLS(DA) and (sparse)(R)GCCA(DA) | 0.3.0 | 16.04 | |
| provides variables representation for (regularized) CCA, (sparse) PLS regression, PCA and (sparse) Regularized generalised CCA | 0.3.0 | 16.04 | |
| plots a correlation circle for the datasets whose correlation circles can be superimposed. This correlation circle contains the selected variables of these datasets which are included in a rectangle and the response variables. | 0.3.0 | 16.04 | |
| performs the computation of the similarities. The similarity between two variables is an approximation of the correlation between these two variables. | 0.3.0 | 16.04 | |
| computes all the correlations needed to plot a correlation circle and determines which correlation circles can be superimposed | 0.3.0 | 16.04 | |
| creates a network between selected variables of datasets and the response variables. In the network, the similarity between two variables is associated with the link between these two variables. | 0.4.0 | 16.04 | |