cluster_by_igraph: Cluster similarity matrix by graph community detection...

In simplifyEnrichment: Simplify Functional Enrichment Results

Description

Cluster similarity matrix by graph community detection methods

Usage

cluster_by_igraph(mat,
    method = c("cluster_fast_greedy",
    "cluster_leading_eigen",
    "cluster_louvain",
    "cluster_walktrap"),
    ...)

Arguments

mat	The similarity matrix.
method	The community detection method.
...	Other arguments passed to the corresponding community detection function, see Details.

Details

The symmetric similarity matrix can be treated as an adjacency matrix and constructed as a graph/network with the similarity values as the weight of hte edges. Thus, clustering the similarity matrix can be treated as detecting clusters/modules/communities from the graph.

Four methods implemented in igraph package can be used here:

cluster_fast_greedy

uses cluster_fast_greedy.

cluster_leading_eigen

uses cluster_leading_eigen.

cluster_louvain

uses cluster_louvain.

cluster_walktrap

uses cluster_walktrap.

Value

A vector of cluster labels (in numeric).

Examples

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simplifyEnrichment documentation built on Nov. 8, 2020, 5:07 p.m.