Link communities R package

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:

The panel on the left shows a 'Spencer circle' layout, while the panel on the right shows a Fruchterman-Reingold layout. From the linkcomm documentation.

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.

Published by

Sune Lehmann

I’m an Associate Professor at the Department of Applied Mathematics and Computer Science, at the Technical University of Denmark.

2 thoughts on “Link communities R package”

  1. 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.

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