View source: R/calculate_variance_explained.R
plot_variance_explained_per_feature | R Documentation |
Plot variance explained by the model for a set of features
Returns a tile plot with a group on the X axis and a feature along the Y axis
plot_variance_explained_per_feature(
object,
view,
features = 10,
split_by_factor = FALSE,
group_features_by = NULL,
groups = "all",
factors = "all",
min_r2 = 0,
max_r2 = NULL,
legend = TRUE,
return_data = FALSE,
...
)
object |
a |
view |
a view name or index. |
features |
a vector with indices or names for features from the respective view, or number of top features to be fetched by their loadings across specified factors. "all" to plot all features. |
split_by_factor |
logical indicating whether to split R2 per factor or plot R2 jointly |
group_features_by |
column name of features metadata to group features by |
groups |
a vector with indices or names for sample groups (default is all) |
factors |
a vector with indices or names for factors (default is all) |
min_r2 |
minimum variance explained for the color scheme (default is 0). |
max_r2 |
maximum variance explained for the color scheme. |
legend |
logical indicating whether to add a legend to the plot (default is TRUE). |
return_data |
logical indicating whether to return the data frame to plot instead of plotting |
... |
extra arguments to be passed to |
ggplot object
# Using an existing trained model
file <- system.file("extdata", "model.hdf5", package = "MOFA2")
model <- load_model(file)
plot_variance_explained_per_feature(model, view = 1)
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