I am doing some work the Rgraphviz, a Bioconductor package, but since my question is of a more general nature, thought I would send to this list in hopes that a graph theory expert could answer my question.
I wish to do some statistics on node-node relationships. In particular, I want to see if two connected nodes share a common property. I believe that the more "connected" the two nodes are the more likely it would be that they share the property. The graph is highly connected, with a large majority of nodes connected in some fashion. My first question is: can anyone make this real easy and tell me if this has been done and how? If not, I need to start with developing a measure of connectedness that includes degrees of separation and number of edges at each degree. The highest level of connectivity, with weighting 1, would be a first order connection (the graph is undirected). Beyond that, of course, it gets more complicated. To begin, I need to identify the best path between two nodes then characterize that path. Rgraphviz seems to have a fair amount of rendering capabilities, but I don't see many functions to statistically analyze the graph. Thanks, Mark -- Mark W. Kimpel MD ** Neuroinformatics ** Dept. of Psychiatry Indiana University School of Medicine 15032 Hunter Court, Westfield, IN 46074 (317) 490-5129 Work, & Mobile & VoiceMail (317) 204-4202 Home (no voice mail please) mwkimpel<at>gmail<dot>com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
