overlap_community {CEMiTool} | R Documentation

## Generates communities from edgelist

### Description

Returns communities from edgelist created by cemoverlap function.

### Usage

    overlap_community(mod_intersection_df, presence_as_weights = FALSE,
      smallest_community = 15, method = c("cluster_fast_greedy",
      "cluster_edge_betweenness", "cluster_label_prop",
      "cluster_leading_eigen", "cluster_louvain", "cluster_optimal",
      "cluster_spinglass", "cluster_walktrap"))

### Arguments

`mod_intersection_df` | Module intersection dataframe obtained from cemoverlap function
`presence_as_weights` | Logical. Should sums of node pair occurence be considered edge weights?
`smallest_community` | Minimal number of genes in community (default:15)
`method` | Character string denoting an `igraph` package clustering function. One of 'cluster_fast_greedy', 'cluster_edge_betweenness', 'cluster_fast_greedy', 'cluster_label_prop', 'cluster_leading_eigen', 'cluster_louvain', 'cluster_optimal', 'cluster_spinglass' or 'cluster_walktrap'. Default: 'cluster_fast_greedy'

### Details

Function takes edgelist as inputs and generates communities using functions provided in igraph package (default:'cluster_fast_greedy')

### Value

A list containing the genes present in each community detected

### Examples

    ## Not run:
    # Run the cemitool function twice on expr dataset. Each time, one sample will be removed
    data(expr0)
    set.seed(10)
    dset1 <- expr0[,-sample(1:ncol(expr0), 1)]
    dset2 <- expr0[,-sample(1:ncol(expr0), 1)]
    cem1 <- cemitool(dset1, plot=FALSE)
    cem2 <- cemitool(dset2, plot=FALSE)
    cem_overlap_df <- cem_overlap(list(cem1, cem2))
    comm_overlap_df <- overlap_community(cem_overlap_df)

    ## End(Not run)

[Package CEMiTool version 1.6.11 Index]