\HeaderA{SCCgraph}{Combines Strongly Connected Components into single nodes}{SCCgraph}
\keyword{graphs}{SCCgraph}
\begin{Description}\relax
\code{SCCgraph} is used to identify all nodes which are not distinguishable given the data.
\end{Description}
\begin{Usage}
\begin{verbatim}
SCCgraph(x,name=TRUE,nlength=20)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] graphNEL object or an adjacency matrix
\item[\code{name}] Concatenate all names of summarized nodes, if TRUE, or number nodes, if FALSE. Default: TRUE
\item[\code{nlength}] maximum length of names
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
A graph inferred by either \code{nem} or \code{nemModelSelection} may have cycles if some phenotypic profiles are not distinguishable.
The function \code{SCCgraph} identifies cycles in the graph (the strongly conneced components) and summarizes them in a single node.
The resulting graph is then acyclic.
\end{Details}
\begin{Value}
\begin{ldescription}
\item[\code{graph}] a graphNEL object with connected components of the input graph summarized into single nodes
\item[\code{scc}] a list mapping SCCs to nodes
\item[\code{which.scc}] a vector mapping nodes to SCCs
\end{ldescription}
\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{transitive.reduction}{transitive.reduction}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
   data("BoutrosRNAi2002")
   D   <- BoutrosRNAiDiscrete[,9:16]
   res <- nem(D,control=set.default.parameters(unique(colnames(D)), para=c(.13,.05)))
   # 
   sccg <- SCCgraph(res$graph,name=TRUE)
   #
   par(mfrow=c(1,2))
   plot.nem(res, main="inferred from data")
   plot(sccg$graph, main="condensed (rel,key)")
\end{ExampleCode}
\end{Examples}

