linkcomm provides tools for the generation, visualization, and analysis of link communities in networks of arbitrary size and type.
Details
Link communities reveal the nested and overlapping structure in networks, and uncover the key nodes that form connections to multiple communities. linkcomm provides tools for generating, visualizing, and analysing link communities in networks of arbitrary size and type.
For a more detailed overview of how to use the package:
Ahn, Y.Y., Bagrow, J.P., and Lehmann, S. (2010). Link communities reveal multiscale complexity in networks. Nature466, 761-764.
Becker, E., Robisson, B., Chapple, C.E., Guenoche, A. and Brun, C. (2012) Multifunctional proteins revealed by overlapping clustering in protein interaction network. Bioinformatics28, 84-90.
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. Bioinformatics27, 2011-2012.
## Generate graph and extract link communities.
g <- swiss[,3:4]
lc <- getLinkCommunities(g)
## Plot a graph layout of the link communities.
plot(lc, type = "graph")
## Use a Spencer circle layout.
plot(lc, type = "graph", layout = "spencer.circle")
## Calculate a community-based measure of node centrality.
getCommunityCentrality(lc)
## Find nested communities.
getAllNestedComm(lc)
## Uncover the relatedness between communities.
getClusterRelatedness(lc)