inetwork-package {inetwork} | R Documentation |
inetwork
implements a network partitioning algorithm to identify communities (or modules) in a network. The network plotting function then utilizes the identified community structure to position the vertices for plotting. The package also contains functions to calculate the assortativity, i.e. degree correlation, and transitivity, i.e. clustering coefficient, of a vertex.
Package: | inetwork |
Type: | Package |
Version: | 1.0 |
Date: | 2007-06-22 |
License: | LGPL |
Identification of communities (or modules) in an undirected network (or graph) by icommunity
, followed by organizing the communities within communities by ihierarchy
and plotting of the network by inetplot
. iassortativity
and itransitivity
in the package calculate a vertex's degree-correlation and clustering coefficient.
Sun-Chong Wang
Institute of Systems Biology and Bioinformatics, National Central University, Taiwan
Epigenetics Laboratory, Centre for Addiction and Mental Health, Toronto Canada
Maintainer: Sun-Chong Wang <sun-chong_wang@camh.net>
M.E.J. Newman, Modularity and community structure in networks, Proc. Natl. Acad. Sci. U.S.A. 103 (2006) 8577–8582.
icommunity
, ihierarchy
, inetplot
, iassortativity
, itransitivity
## load data data(icashflow) ## network partitioning to find communities ihierarchy(icommunity(cf5)) ## network plotting showing the communities inetplot(icommunity(cf5,partite=TRUE))