\HeaderA{hyperGTest}{Hypergeometric Tests for GO term association}{hyperGTest}
\aliasA{hyperGTest,GOHyperGParams-method}{hyperGTest}{hyperGTest,GOHyperGParams.Rdash.method}
\keyword{models}{hyperGTest}
\begin{Description}\relax
Given a \code{GOHyperGParams} instance
containing a set of unique Entrez Gene Identifiers, a microarray
annotation data package name, and the GO ontology of interest, this
function will compute Hypergeomtric p-values for over or
under-representation of each GO term in the specified ontology among
the GO annotations for the interesting genes.  The computations can
be done conditionally based on the structure of the GO graph.
\end{Description}
\begin{Arguments}
\begin{ldescription}
\item[\code{p}] A \code{GOHyperGParams} instance 
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
When \code{conditional(p) == TRUE}, the \code{hyperGTest} function
uses the structure of the GO graph to estimate for each term whether
or not there is evidence beyond that which is provided by the term's
children to call the term in question statistically overrepresented.

The algorithm conditions on all child terms that are themselves
significant at the specified p-value cutoff.  Given a subgraph of
one of the three GO ontologies, the terms with no child categories
are tested first.  Next the nodes whose children have already been
tested are tested.  If any of a given node's children tested
significant, the appropriate conditioning is performed.
\end{Details}
\begin{Value}
A \code{GOHyperGResult} instance.
\end{Value}
\begin{Author}\relax
Seth Falcon
\end{Author}
\begin{References}\relax
FIXME
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{GOHyperGResult-class}{GOHyperGResult.Rdash.class}}
\code{\LinkA{geneCategoryHyperGeoTest}{geneCategoryHyperGeoTest}}
\code{\LinkA{geneGoHyperGeoTest}{geneGoHyperGeoTest}}
\code{\LinkA{geneKeggHyperGeoTest}{geneKeggHyperGeoTest}}
\end{SeeAlso}

