Description Details Note Author(s) References Examples

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.

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.

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

Martin L. Jäger

*Maintainer:* Ronja Foraita <[email protected]>

Leibniz Institute for Prevention Research and Epidemiology (BIPS)

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

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```
$K
[1] 3
$n.iterations
[1] 14
$Cluster
[1] 1 1 1 1 2 2 2 0 0
```

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