\HeaderA{plot.nem}{plot nested effect model}{plot.nem}
\aliasA{plot.ModuleNetwork}{plot.nem}{plot.ModuleNetwork}
\methaliasA{plot.nem.BN}{plot.nem}{plot.nem.BN}
\methaliasA{plot.nem.bootstrap}{plot.nem}{plot.nem.bootstrap}
\methaliasA{plot.nem.consensus}{plot.nem}{plot.nem.consensus}
\methaliasA{plot.nem.greedy}{plot.nem}{plot.nem.greedy}
\methaliasA{plot.nem.greedyMAP}{plot.nem}{plot.nem.greedyMAP}
\methaliasA{plot.nem.jackknife}{plot.nem}{plot.nem.jackknife}
\aliasA{plot.pairwise}{plot.nem}{plot.pairwise}
\aliasA{plot.score}{plot.nem}{plot.score}
\aliasA{plot.triples}{plot.nem}{plot.triples}
\aliasA{plotnem}{plot.nem}{plotnem}
\keyword{models}{plot.nem}
\begin{Description}\relax
plot graph of nested effects model, the marginal likelihood distribution or the posterior position of the effected genes
\end{Description}
\begin{Usage}
\begin{verbatim}
        ## S3 method for class 'nem':
        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",...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] nem object to plot
\item[\code{what}] (i), "graph", (ii) "mLL" = likelihood distribution, (iii) "pos" = posterior position of effected genes
\item[\code{remove.singletons}] remove unconnected nodes from the graph plot
\item[\code{PDF}] output as PDF-file
\item[\code{filename}] filename of PDF-file
\item[\code{thresh}] if x has a real valued adjacency matrix (weight matrix),  don't plot edges with \textbar{}weight\textbar{} \textless{}= thresh
\item[\code{transitiveReduction}] plot a transitively reduced graph
\item[\code{plot.probs}] plot edge weights/probabilities. If regulation directions have been inferred (see \code{infer.edge.type}), upregulated edges are drawn red and downregulated edges blue. Edges, were no clear direction could be inferred, are drawn in black.
\item[\code{SCC}] plot the strongly connected components graph
\item[\code{D}] Visualize the nested subset structure of the dataset via \code{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
\item[\code{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
\item[\code{palette}] color palette to use: either 'BlueRed' (default) or 'Grey'
\item[\code{...}] other arguments to be passed to the Rgraphviz plot function or to the graphics 'image' function.
\end{ldescription}
\end{Arguments}
\begin{Value}
none
\end{Value}
\begin{Author}\relax
Florian Markowetz \textless{}URL: http://genomics.princeton.edu/\textasciitilde{}florian\textgreater{}, Holger Froehlich \textless{}URL: http://www.dkfz.de/mga2/people/froehlich\textgreater{}
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{nem}{nem}}, \code{\LinkA{plotEffects}{plotEffects}}, \code{\LinkA{infer.edge.type}{infer.edge.type}}
\end{SeeAlso}

