Clustering Method Stability Facet Plot — plot_clustering_difference

Display the distribution of the EC consistency for each clustering method and each resolution value on a given embedding The all field of the object returned by the get_clustering_difference_object method is used.

plot_clustering_difference_facet(
  clust_object,
  embedding,
  low_limit = 0,
  high_limit = 1,
  grid = TRUE
)

Arguments

clust_object: An object returned by the assess_clustering_stability method.
embedding: An embedding (only the first two dimensions will be used for visualization).
low_limit: The lowest value of ECC that will be displayed on the embedding.
high_limit: The highest value of ECC that will be displayed on the embedding.
grid: Boolean value indicating whether the facet should be a grid (where each row is associated with a resolution value and each column with a clustering method) or a wrap.

Value

A ggplot2 object. #TODO should export

Examples

# FIXME fix the examples
# set.seed(2021)
# # create an artificial PCA embedding
# pca_embedding <- matrix(runif(100 * 30), nrow = 100)
# rownames(pca_embedding) <- as.character(1:100)
# colnames(pca_embedding) <- paste0("PCA_", 1:30)

# adj_matrix <- Seurat::FindNeighbors(pca_embedding,
#     k.param = 10,
#     nn.method = "rann",
#     verbose = FALSE,
#     compute.SNN = FALSE
# )$nn
# clust_diff_obj <- assess_clustering_stability(
#     graph_adjacency_matrix = adj_matrix,
#     resolution = c(0.5, 1),
#     n_repetitions = 10,
#     algorithm = 1:2,
#     verbose = FALSE
# )
# plot_clustering_difference_facet(clust_diff_obj, pca_embedding)