cluster_methods: Configure clustering methods

In jokergoo/simplifyGO: Simplify Functional Enrichment Results

Configure clustering methods

Description

Configure clustering methods

Usage

register_clustering_methods(...)

all_clustering_methods()

remove_clustering_methods(method)

reset_clustering_methods()

Arguments

...	A named list of clustering functions, see in Details.
method	A vector of method names.

Details

The user-defined functions should accept at least one argument which is the input matrix. The second optional argument should always be ... so that parameters for the clustering function can be passed by the control argument from cluster_terms(), simplifyGO() or simplifyEnrichment(). If users forget to add ..., it is added internally.

Please note, the user-defined function should automatically identify the optimized number of clusters.

The function should return a vector of cluster labels. Internally it is converted to numeric labels.

The default clustering methods are:

• kmeans see cluster_by_kmeans().

• dynamicTreeCut see cluster_by_dynamicTreeCut().

• mclust see cluster_by_mclust().

• 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().

Value

all_clustering_methods() returns a vector of clustering method names.

Examples

register_clustering_methods(
    # assume there are 5 groups
    random = function(mat, ...) sample(5, nrow(mat), replace = TRUE)
)
all_clustering_methods()
remove_clustering_methods("random")
all_clustering_methods()
remove_clustering_methods(c("kmeans", "mclust"))
all_clustering_methods()
reset_clustering_methods()
all_clustering_methods()

jokergoo/simplifyGO documentation built on Sept. 18, 2024, 9:45 p.m.