cluster_by_igraph {simplifyEnrichment} | R Documentation

## Cluster similarity matrix by graph community detection methods

### 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

    # There is no example
    NULL

[Package simplifyEnrichment version 1.4.0 Index]