1. Lightning talk to Boston area R users group Jeff Marcus 7/13/2011
Rgraphviz
Lightning talk to Boston area R users group Jeff Marcus 7/13/2011

2. Introduction Rgraphviz allows you to visualize graphs (nodes and arcs)
Good detailed presentation at
Some applications
Social networks
Biological pathways, protein interactions
My use: callflow analysis in speech recognition applications
Rgraphviz part of Bioconductor project
Built around Graphviz, AT&T opensource graph visualization software

3. Example using “graph” package
library(“graph”) library(“Rgraphviz”) nodes <- c("A", "B", "C", "D")
edge.list <- list( A=list(edges=c("A", "B", "C")), B=list(edges=("C")), C=list(edges=c(“C","D")), D=list(edges=“B")) g <- new("graphNEL", nodes=nodes, edgeL=edge.list, edgemode="directed")
Rgraphviz::plot(g)
Note: graphNEL is a class in the “graph” package that extends virtual “graph” class. Efficient for smallish graphs with not too many edges

4. Igraph package
Package “igraph” has richer set of graph manipulation functions and is better suited to large graphs
Must convert igraph to graphNEL for Rgraphviz
library(“igraph”) # igraph has many ways to construct graphs ig <- igraph::graph.data.frame (data.frame( from=c("a","a","a","b", "c", "c", "d"), to=c("a","b","c","c", "c", "d", "b"))) g <- igraph.to.graphNEL (ig) # Same graph as before Rgraphviz::plot(g)

5. Rgraphviz layout control
Very fine-grained control of layout
Overall layout (“dot”, “neato”, etc., each useful for different purposes)
Node shapes
Node and edge colors
Edge thicknesses
Ability to plot subgraphs as well
Rgraphviz essentially an API around graphviz so need to consult graphviz documentation for details
Caution: I found that many but not all graphviz features supported

6. Example: callflow graph
Rgraphviz can produce legible graphs much more complex than this one

7. Installation You will need to first install graphviz
See for details for Windows installation.