View source: R/stability-1-dim-reduction.R
plot_feature_overall_stability_boxplot | R Documentation |
Display EC consistency for each feature set and for each step.
Above each boxplot there is a number representing
the step (or the size of the subset). The ECC values are extracted for each
resolution value and summarized using the summary_function
parameter.
plot_feature_overall_stability_boxplot(
feature_object_list,
summary_function = stats::median,
text_size = 4,
boxplot_width = 0.4,
dodge_width = 0.7,
return_df = FALSE
)
feature_object_list |
An object or a concatenation of objects returned
by the |
summary_function |
The function that will be used to summarize the ECC
values. Defaults to |
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 |
dodge_width |
Used for adjusting the horizontal position of the boxplot;
the value will be passed to the |
return_df |
If TRUE, the function will return the ECS values as a
dataframe. Default is |
A ggplot2 object.
set.seed(2024)
# create an artificial expression matrix
expr_matrix <- matrix(
c(runif(100 * 10), runif(100 * 10, min = 3, max = 4)),
nrow = 200, byrow = TRUE
)
rownames(expr_matrix) <- as.character(1:200)
colnames(expr_matrix) <- paste("feature", 1:10)
feature_stability_result <- assess_feature_stability(
data_matrix = t(expr_matrix),
feature_set = colnames(expr_matrix),
steps = 5,
feature_type = "feature_name",
resolution = c(0.1, 0.5, 1),
n_repetitions = 10,
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_boxplot(feature_stability_result)
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