\HeaderA{makeGOGraph}{Construct a GO Graph}{makeGOGraph}
\keyword{manip}{makeGOGraph}
\begin{Description}\relax
The directed acyclic graph (DAG) based on finding the most specific
terms for the supplied LocusLink IDs is constructed and returned. The
constructuion is per GO ontology (there are three, MF, BP and CC) and
once the most specific terms have been identified then all less
specific terms are found (these are the parents of the terms) and then
their parents and so on, until the root is encountered.
\end{Description}
\begin{Usage}
\begin{verbatim}
makeGOGraph(x, Ontology="MF", removeRoot = TRUE)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] A vector of LocusLink IDs. 
\item[\code{Ontology}] Which of the GO ontologies to use. 
\item[\code{removeRoot}] A logical value indicating whether the GO root nood
should be removed or not.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
For each supplied LocusLink identifier all the GO annotations (in the
specified ontology) are found.

The mappings are different for the different ontologies. Typically a
GO indentifier is used only in one specific ontology.

The resulting structure is stored in a graph using the \code{graph}
package, again from Bioconductor.
\end{Details}
\begin{Value}
An object that inherits from the \code{graph} class. The particular
implementation is not specified.
\end{Value}
\begin{Author}\relax
R. Gentleman
\end{Author}
\begin{References}\relax
The Gene Ontology Consortium
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{oneGOGraph}{oneGOGraph}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
 gN <- c("71733","224019", "237928", "11308")
 gg1 <- makeGOGraph(gN, "BP")
 
\end{ExampleCode}
\end{Examples}

