Compare clustering methods

Usage

compare_clustering_methods(
  mat,
  method = setdiff(all_clustering_methods(), "mclust"),
  plot_type = c("mixed", "heatmap"),
  nrow = 3,
  verbose = TRUE
)

Arguments

mat: The similarity matrix.
method: Which methods to compare. All available methods are in all_clustering_methods. A value of all takes all available methods. By default mclust is excluded because its long runtime.
plot_type: See explanation in cmp_make_plot.
nrow: Number of rows of the layout when plot_type is set to heatmap.
verbose: Whether to print messages.

Value

No value is returned.

Details

The function compares following clustering methods by default:

-kmeans see cluster_by_kmeans. -pam see cluster_by_pam. -dynamicTreeCut see cluster_by_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_fast_greedy. -louvain see cluster_by_louvain. -walktrap see cluster_by_walktrap. -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.

Examples

# \donttest{
mat = readRDS(system.file("extdata", "random_GO_BP_sim_mat.rds",
    package = "simplifyEnrichment"))
compare_clustering_methods(mat)
#> Cluster 500 terms by 'kmeans'...
#>  18 clusters, used 3.221053 secs.
#> Cluster 500 terms by 'pam'...
#>  5 clusters, used 20.67218 secs.
#> Cluster 500 terms by 'dynamicTreeCut'...
#>  60 clusters, used 0.132031 secs.
#> Cluster 500 terms by 'apcluster'...
#>  41 clusters, used 0.7050171 secs.
#> Cluster 500 terms by 'hdbscan'...
#>  14 clusters, used 0.163321 secs.
#> Cluster 500 terms by 'fast_greedy'...
#>  6 clusters, used 0.06812 secs.
#> Cluster 500 terms by 'louvain'...
#>  6 clusters, used 0.07268381 secs.
#> Cluster 500 terms by 'walktrap'...
#>  6 clusters, used 0.780349 secs.
#> Cluster 500 terms by 'MCL'...
#>  6 clusters, used 1.736204 secs.
#> Cluster 500 terms by 'binary_cut'...
#>  19 clusters, used 4.215953 secs.

compare_clustering_methods(mat, plot_type = "heatmap")
#> Cluster 500 terms by 'kmeans'...
#>  23 clusters, used 3.011423 secs.
#> Cluster 500 terms by 'pam'...
#>  5 clusters, used 20.29424 secs.
#> Cluster 500 terms by 'dynamicTreeCut'...
#>  60 clusters, used 0.13887 secs.
#> Cluster 500 terms by 'apcluster'...
#>  41 clusters, used 0.7265048 secs.
#> Cluster 500 terms by 'hdbscan'...
#>  14 clusters, used 0.1619201 secs.
#> Cluster 500 terms by 'fast_greedy'...
#>  6 clusters, used 0.061584 secs.
#> Cluster 500 terms by 'louvain'...
#>  6 clusters, used 0.0815661 secs.
#> Cluster 500 terms by 'walktrap'...
#>  6 clusters, used 0.2488348 secs.
#> Cluster 500 terms by 'MCL'...
#>  6 clusters, used 1.787284 secs.
#> Cluster 500 terms by 'binary_cut'...
#>  19 clusters, used 5.14202 secs.

# }