calculate_variance_explained_per_sample {MOFA2} | R Documentation |
This function takes a trained MOFA model as input and calculates, **for each sample** the proportion of variance explained (i.e. the coefficient of determinations (R^2)) by the MOFA factors across the different views.
calculate_variance_explained_per_sample( object, views = "all", groups = "all", factors = "all" )
object |
a |
views |
character vector with the view names, or numeric vector with view indexes. Default is 'all' |
groups |
character vector with the group names, or numeric vector with group indexes. Default is 'all' |
factors |
character vector with the factor names, or numeric vector with the factor indexes. Default is 'all' |
a list with matrices with the amount of variation explained per sample and view.
# Using an existing trained model on simulated data file <- system.file("extdata", "model.hdf5", package = "MOFA2") model <- load_model(file) # Calculate variance explained (R2) r2 <- calculate_variance_explained_per_sample(model)