| plotVarianceExplained {MOFA} | R Documentation |
Method to plot variance explained (R-squared) by the MOFA model for each view and latent factor.
As a measure of variance explained for gaussian data we adopt the coefficient of determination (R2).
For details on the computation see the help of the calculateVarianceExplained function
plotVarianceExplained(object, cluster = TRUE, ...)
object |
a |
cluster |
logical indicating whether to do hierarchical clustering on the plot |
... |
extra arguments to be passed to |
ggplot object
# Using an existing trained model on the CLL data
filepath <- system.file("extdata", "CLL_model.hdf5", package = "MOFAdata")
MOFA_CLL <- loadModel(filepath)
plotVarianceExplained(MOFA_CLL)
# Using an existing trained model on the scMT data
filepath <- system.file("extdata", "scMT_model.hdf5", package = "MOFAdata")
MOFA_scMT <- loadModel(filepath)
plotVarianceExplained(MOFA_scMT)