get_groups_based_on_clustering: get_groups_based_on_clustering

In haneylab/geNet: Generating large network of co-occurring genes

Description

function to get the groups based on a clustering algorithm Note: the color of the nodes is based on the group (using the function get_new_colors_based_on_groups()) to evaluate the clustering method we use the modularity measure. The modularity of a graph with respect to some division (or vertex types) measures how good the division is, or how separated are the different vertex types from each other.

Usage

get_groups_based_on_clustering(igraph_network, method = "infomap")

Arguments

igraph_network

igraph network generated by the gen_igraph_network() function. Mandatory argument.

method

clustering method: louvain: predict clusters using the Louvain algorithm. The "modularity" is the objective function to maximize. Small clusters may be hidden. It detects only the bigger clusters. infomap: predict clusters using the Infomap algorithm. The "map equation" is the objective function to minimize. Compared to the Louvain algorithm, it is able to identify smaller clusters (subclusters) fastgreedy: predicts clusters using the Fastgreedy algorithm walktrap: predicts clusters using the Walktrap algorithm Default to "infomap" to detect smaller clusters. The Louvain algorithm is faster than the Infomap algorithm in large networks.

Value

Object of class "dataframe", which reports the genes ID associated with the new groups

Examples

## Not run: get_groups_based_on_clustering(igraph_network,method="infomap")

haneylab/geNet documentation built on Oct. 4, 2020, 8:40 a.m.