MCL-package: Markov Cluster Algorithm

Description Details Note Author(s) References Examples

Description

Contains the Markov cluster algorithm (MCL) by van Dongen (2000) for identifying clusters in networks and graphs. The algorithm simulates random walks on a (n x n) matrix as the adjacency matrix of a graph. It alternates an expansion step and an inflation step until an equilibrium state is reached.

Details

Package: MCL
Type: Package
Version: 1.0
Date: 2015-03-10
License: GPL-2 | GPL-3 [expanded from: GPL (= 2)]

The Markov Cluster Algorithm (MCL) is a method to identify clusters in undirected network graphs. It is suitable for high-dimensional data (e.g. gene expression data).

The original MCL uses the adjacency matrix of a graph (propsed by van Dongen (2000)). The function mcl in this package allows in addition the input of a (n x n) matrix.

Note

We thank Moritz Hanke for his help in realizing this package.

Author(s)

Martin L. Jäger

Maintainer: Ronja Foraita <foraita@bips.uni-bremen.de>
Leibniz Institute for Prevention Research and Epidemiology (BIPS)

References

van Dongen, S.M. (2000) Graph Clustering by Flow Simulation. Ph.D. thesis, Universtiy of Utrecht. Utrecht University Repository: http://dspace.library.uu.nl/handle/1874/848

Examples

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### Load adjacency matrix
adjacency <- matrix(c(0,1,1,1,0,0,0,0,0,1,0,1,1,1,0,0,0,0,1,1,
             0,1,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,1,0,0,0,1,1,0,
             0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,
             0,0,0,0,0,0,0,0,0,0,0,0,0), byrow=TRUE, nrow=9)

### Run MCL 
mcl(x = adjacency, addLoops = TRUE )

MCL documentation built on May 29, 2017, 10:59 a.m.