| MCL-package {MCL} | R Documentation |
Markov Cluster Algorithm
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
### 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 )