View source: R/stability-3-graph-clustering.R
plot_clustering_difference_facet | R Documentation |
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
)
clust_object |
An object returned by the
|
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. |
A ggplot2 object. #TODO should export
# 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)
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