Plot component stability as a function of the number of components

Plots the results of estimateStability. See this function's documentation for more information.

Usage

plotStability(
  stability,
  plot_path = NULL,
  stability_threshold = NULL,
  mean_stability_threshold = NULL,
  height = 4,
  width = 10,
  ...
)

Arguments

stability

The results of estimateStability.

plot_path

The path at which the plot will be saved

stability_threshold

Plots a stability threshold, below which components can be pruned by runICA.

mean_stability_threshold

Plots a stability threshold, which is used by estimateStability to provide a naive estimate for the optimal number of components.

height

The height of the plot, to be passed to ggsave.

width

The width of the plot, to be passed to ggsave.

...

Additional arguments to be passed to ggsave.

Value

Returns a list of three plots as ggplot2 objects:

combined_plot

The two other plots combined with patchwork.

stability_plot

A plot in which each line indicates stability as a function of the number of components. A line is shown for each number of components tested.

mean_plot

The average component stability as a function of the number of components.

Author

Jack Gisby

Examples

# Get a random matrix with rnorm, with 200 rows (features)
# and 100 columns (observations)
X <- ReducedExperiment:::.makeRandomData(200, 100, "feature", "obs")

# Estimate stability across 10 to 30 components
stab_res <- estimateStability(
    X,
    min_components = 10,
    max_components = 30,
    n_runs = 5,
    verbose = FALSE
)

# Intracluster stability similar to extracluster since this is random data
plotStability(stab_res)$combined_plot