ggm.make.graph {GeneNet} | R Documentation |
ggm.make.dot
converts an edge list as obtained by ggm.test.edges
into a "dot" file that can directly be used for plotting the network with graphviz.
network.make.dot
is just an alias to ggm.make.dot
.
ggm.make.graph
converts an edge list as obtained by ggm.test.edges
into a graph object.
show.edge.weights
summarizes a graph object by prints a vector of weights for all
edges contained in a graph.
This function is convenient to gain a first impression of the graph (in particular if
the "Rgraphviz" library is not installed).
ggm.make.dot(filename, edge.list, node.labels, main=NULL, show.edge.labels=FALSE) network.make.dot(filename, edge.list, node.labels, main=NULL, show.edge.labels=FALSE) ggm.make.graph(edge.list, node.labels, drop.singles=FALSE) show.edge.weights(gr)
filename |
name of file containg the "dot" commands for graphviz |
edge.list |
a data frame, as obtained by ggm.test.edges , listing all
edges to be included in the graph |
node.labels |
a vector with labels for each node (will be converted to type character) |
main |
title included in plot |
show.edge.labels |
plot correlation values as edge labels (default: FALSE) |
drop.singles |
remove unconnected nodes |
gr |
a graph object |
... |
options passed to plot functions |
For network plotting the software "graphviz" is employed (http://www.graphviz.org).
For the functions ggm.plot.graph
and ggm.make.graph
the "graph" and "Rgraphviz"
infrastructure from the Bioconductor project (http://www.bioconductor.org) is required.
ggm.make.dot
produces a "dot" network description file that
can directly be fed into graphviz in order to produce a plot of a network.
ggm.make.graph
returns a graph object, suitable for plotting with functions from
the "Rgraphviz" library.
show.edge.weights
returns a vector of weights for all edges contained in a graph.
Juliane Sch"afer, Rainer Opgen-Rhein, and Korbinian Strimmer (http://strimmerlab.org).
ggm.test.edges
, plot.graph
.
# load GeneNet library library("GeneNet") # generate random network with 20 nodes and 10 percent edges (=19 edges) true.pcor <- ggm.simulate.pcor(20, 0.1) # convert to edge list test.results <- ggm.list.edges(true.pcor)[1:19,] ######## use graphviz directly to produce a plot ########## # uncomment for actual use! # nlab <- LETTERS[1:20] # ggm.make.dot(filename="test.dot", test.results, nlab, main = "A graph") # system("fdp -T svg -o test.svg test.dot") # SVG format ######## use Rgraphviz produce a plot ########## # uncomment for actual use! # nlab <- LETTERS[1:20] # gr <- ggm.make.graph( test.results, nlab) # gr # show.edge.weights(gr) # gr2 <- ggm.make.graph( test.results, nlab, drop.singles=TRUE) # gr2 # plot network # NOTE: this requires the installation of the "Rgraphviz" library # library("Rgraphviz") # plot(gr)