A while ago, I wrote about Rob Spencer over at Scaled Innovation‘s implementation of the algorithm for detecting link communities. Today, I am happy to report on another exciting development for the alorithm. Alex Kalinka from the Tomancak lab at the Max Plank Institute (MPI-CBG) has written a great implementation in R, called linkcomm. It is now up on CRAN:
http://cran.r-project.org/web/packages/linkcomm/index.html
While everything is excellent, the graphics are particularly beautiful – much prettier than our own visualizations – check out the colored link dendrogram plot (from the CRAN website)
And the spatial network layout options are great as well; the various community visualizations are simple, elegant, and very pretty:
In addition, there are many neat features. For example, linkcomm allows you to visualize sub-communities by themselves. Alex has also published an Application Note in Bioinformatics about the implementation, so take a look if you’re interested:
http://bioinformatics.oxfordjournals.org/content/early/2011/05/19/bioinformatics.btr311.abstract (open access).
We also link to the package from our link communities download page.
sune lehmann 
2 responses to “Link communities R package”
I am interested in radial network visualization. I haven’t made GraphViz twopi work particular well. I am looking for a program that does a better layout than the bullseye visualization I have done:
I wonder about Spencer layout I haven’t heard of that before.
Hey Finn,
Thanks for the comments.
Check out http://www.win.tue.nl/~dholten/papers/bundles_infovis.pdf for super cool radial layouts (esp Fig 13.)
The ‘Spencer’ layout is the one Rob Spencer came up with for link clustering see https://sunelehmann.com/2010/11/03/visualizing-link-communities/ for details.