louvain: Louvain community detection

In mzinkgraf/fastOC: Co-expression network analysis across multiple species

Description

Run the Louvain clustering method multiple times on a user defined set of edges. For each run, the edgelist is shuffled so the louvain method begins at a random starting point in the network.

Usage

louvain(GeneMeta, edgelist, nruns, nThreads = 1)

Arguments

GeneMeta	Data frame that contains the project metadata. See createGeneMeta
edgelist	A data frame that contains three columns. The first two columns define the edges between gene_A and gene_B. Gene names must be converted to integer values. The third column defines the numeric edge weight.
nruns	An interger defining the number of runs.
nThreads	Integer specifying number of cores to be used by doParallel. Default = 1

Author(s)

Matthew Zinkgraf, [e-mail]

References

Vincent D. Blondel, Jean-Loup Guillaume, Renaud Lambiotte, Etienne Lefebvre. 2008. Fast unfolding of communities in large networks. J. Stat. Mech. P10008

See Also

cluster_louvain

Examples

data("combined_out")
data("GeneMeta")
nRuns = 100
results <- louvain(GeneMeta, edgelist = combined_out, nruns= nRuns)

mzinkgraf/fastOC documentation built on May 13, 2019, 3:01 a.m.