plot_variance_explained: Plot variance explained by the model

In MOFA2: Multi-Omics Factor Analysis v2

Description

plots the variance explained by the MOFA factors across different views and groups, as specified by the user. Consider using cowplot::plot_grid(plotlist = ...) to combine the multiple plots that this function generates.

Usage

plot_variance_explained(
  object,
  x = "view",
  y = "factor",
  split_by = NA,
  plot_total = FALSE,
  factors = "all",
  min_r2 = 0,
  max_r2 = NULL,
  legend = TRUE,
  use_cache = TRUE,
  ...
)

Arguments

object	a MOFA object
x	character specifying the dimension for the x-axis ("view", "factor", or "group").
y	character specifying the dimension for the y-axis ("view", "factor", or "group").
split_by	character specifying the dimension to be faceted ("view", "factor", or "group").
plot_total	logical value to indicate if to plot the total variance explained (for the variable in the x-axis)
factors	character vector with a factor name(s), or numeric vector with the index(es) of the factor(s). 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).
use_cache	logical indicating whether to use cache (default is TRUE)
...	extra arguments to be passed to calculate_variance_explained

Value

A list of ggplot objects (if plot_total is TRUE) or a single ggplot object

Examples

# 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(model)

# Plot variance explained values (view as x-axis, and factor as y-axis)
plot_variance_explained(model, x="view", y="factor")

# Plot variance explained values (view as x-axis, and group as y-axis)
plot_variance_explained(model, x="view", y="group")

# Plot variance explained values for factors 1 to 3
plot_variance_explained(model, x="view", y="group", factors=1:3)

# Scale R2 values
plot_variance_explained(model, max_r2=0.25)

MOFA2 documentation built on Nov. 8, 2020, 7:28 p.m.