Usage
"plot"(x, what="graph", remove.singletons=FALSE, PDF=FALSE, filename="nemplot.pdf", thresh=0, transitiveReduction=FALSE, plot.probs=FALSE, SCC=TRUE, D=NULL, draw.lines=FALSE, palette="BlueRed",...)
Arguments
what
(i), "graph", (ii) "mLL" = likelihood distribution, (iii) "pos" = posterior position of effected genes
remove.singletons
remove unconnected nodes from the graph plot
filename
filename of PDF-file
thresh
if x has a real valued adjacency matrix (weight matrix), don't plot edges with |weight|
transitiveReduction
plot a transitively reduced graph
plot.probs
plot edge weights/probabilities. If regulation directions have been inferred (see infer.edge.type), upregulated edges are drawn red and downregulated edges blue. Edges, were no clear direction could be inferred, are drawn in black.
SCC
plot the strongly connected components graph
D
Visualize the nested subset structure of the dataset via plotEffects along with the graph and show the linking of E-genes to S-genes in the dataset. Should only be used for small networks. Default: Just plot the graph
draw.lines
If the nested subset structure is shown, should additionally lines connecting S-genes and their associated E-genes be drawn? WARNING: For larger datasets than e.g. 5 S-genes this most probably does not work, because the nested subset structure picture then partially overlaps with the graph picture. Default: Do not draw these lines
palette
color palette to use: either 'BlueRed' (default) or 'Grey'
...
other arguments to be passed to the Rgraphviz plot function or to the graphics 'image' function.