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:
kmeans
see cluster_by_kmeans
.
dynamicTreeCut
mclust
see cluster_by_mclust
. By default it is not included.
apcluster
see cluster_by_apcluster
.
hdbscan
see cluster_by_hdbscan
.
fast_greedy
see cluster_by_igraph
.
leading_eigen
see cluster_by_igraph
.
louvain
see cluster_by_igraph
.
walktrap
see cluster_by_igraph
.
MCL
see cluster_by_MCL
.
binary_cut
see 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)