Overall Feature Stability Incremental Boxplot

Perform an incremental ECS between two consecutive feature steps. The ECS values are extracted for every resolution value and summarized using a function (e.g. median, mean, etc.).

Usage

plot_feature_overall_stability_incremental(
  feature_object_list,
  summary_function = stats::median,
  dodge_width = 0.7,
  text_size = 4,
  boxplot_width = 0.4,
  return_df = FALSE
)

Arguments

feature_object_list

An object or a concatenation of objects returned by the assess_feature_stability method.

summary_function

The function used to summarize the ECS values. Default is median.

dodge_width

Used for adjusting the horizontal position of the boxplot; the value will be passed to the width argument of the ggplot2::position_dodge method.

text_size

The size of the labels above boxplots.

boxplot_width

Used for adjusting the width of the boxplots; the value will be passed to the width argument of the ggplot2::geom_boxplot method.

return_df

If TRUE, the function will return the ECS values as a dataframe. Default is FALSE.

Value

A ggplot2 object with ECS distribution will be displayed as a boxplot. Above each boxplot there will be a pair of numbers representing the two steps that are compared.

Examples

set.seed(2024)
# create an artificial expression matrix
expr_matrix <- matrix(
    c(runif(50 * 10), runif(50 * 10, min = 3, max = 4)),
    nrow = 100, byrow = TRUE
)
rownames(expr_matrix) <- as.character(1:100)
colnames(expr_matrix) <- paste("feature", 1:10)

feature_stability_result <- assess_feature_stability(
    data_matrix = t(expr_matrix),
    feature_set = colnames(expr_matrix),
    steps = c(5, 10),
    feature_type = "feature_name",
    resolution = c(0.1, 0.5),
    n_repetitions = 3,
    umap_arguments = list(
        # the following parameters are used by the umap function
        # and are not mandatory
        n_neighbors = 3,
        approx_pow = TRUE,
        n_epochs = 0,
        init = "random",
        min_dist = 0.3
    ),
    clustering_algorithm = 1
)
plot_feature_overall_stability_incremental(feature_stability_result)