cluster: Network clustering

Description

Network clustering based on different methods.

Usage

cluster(graph, method = c("FN", "MCL", "LINKCOMM", "MCODE"), expansion = 2, inflation = 2, hcmethod = "average", directed = FALSE, outfile = NULL, plot = TRUE, layout = c("reingold.tilford", "circle", "random", "fruchterman.reingold", "sphere", "kamada.kawai", "lgl"), ...)

Arguments

graph

An igraph object.

method

Clustering method, possible values are FN, MCL, LINKCOMM and MCODE.

expansion

Numeric value > 1 for the expansion parameter, if method is MCL. See MCL for more information.

inflation

Numeric value > 0 for the inflation power coefficient, if method is MCL. See MCL for more information.

hcmethod

A character string naming the hierarchical clustering method to use. Default value is average. See linkcomm for more information.

directed

Logical value, indicating whether the network is directed (if TRUE) or not (if FLASE).

outfile

File to save the clustering result.

plot

Logical value, indicating whether to plot summary output (if TRUE) or not (if FLASE).

layout

Mode of the layout, possible values are fruchterman.reingold, reingold.tilford, random, circle, kamada.kawai, lgl and sphere. See igraph for more information.

...

Other arguments.

Value

A summary and visulization of the clustering.

References

A Clauset, MEJ Newman, C (2004) Moore: Finding community structure in very large networks, http://www.arxiv.org/abs/cond-mat/0408187.

van Dongen, S.M. (2000) Graph Clustering by Flow Simulation. Ph.D. thesis, Universtiy of Utrecht.

Kalinka, A.T. and Tomancak, P. (2011). linkcomm: an R package for the generation, visualization, and analysis of link communities in networks of arbitrary size and type. Bioinformatics 27 (14), 2011-2012.

Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics. 2003 Jan 13;4(1):2.

Examples

Run this code

nlocal<-data.frame(c("DVL1","DVL2","DVL3"))
net<-construction(input=nlocal,db="HPRD",species="human",ID.type="Gene symbol",hierarchy=1)
cluster(net,method="MCODE",layout="fruchterman.reingold")
cluster(net,method="FN",layout="fruchterman.reingold")