| compare_clustering_methods {simplifyEnrichment} | R Documentation |
Compare clustering methods
compare_clustering_methods(mat, method = setdiff(all_clustering_methods(), "mclust"),
plot_type = c("mixed", "heatmap"), nrow = 3, verbose = TRUE)
mat |
The similarity matrix. |
method |
Which methods to compare. All available methods are in |
plot_type |
See explanation in |
nrow |
Number of rows of the layout when |
verbose |
Whether to print messages. |
The function compares following clustering methods by default:
kmeanssee cluster_by_kmeans.
dynamicTreeCutmclustsee cluster_by_mclust. By default it is not included.
apclustersee cluster_by_apcluster.
hdbscansee cluster_by_hdbscan.
fast_greedysee cluster_by_igraph.
leading_eigensee cluster_by_igraph.
louvainsee cluster_by_igraph.
walktrapsee cluster_by_igraph.
MCLsee cluster_by_MCL.
binary_cutsee binary_cut.
This functon is basically a wrapper function. It calls the following two functions:
cmp_make_clusters: applies clustering with different methods.
cmp_make_plot: makes the plots.
No value is returned.
## Not run:
mat = readRDS(system.file("extdata", "random_GO_BP_sim_mat.rds",
package = "simplifyEnrichment"))
compare_clustering_methods(mat)
compare_clustering_methods(mat, plot_type = "heatmap")
## End(Not run)