\Header{venn}{Venn Diagrams}
\alias{vennCounts}{venn}
\alias{vennDiagram}{venn}
\keyword{htest}{venn}
\begin{Description}\relax
Compute classification counts or plot classification counts in a Venn diagram.
\end{Description}
\begin{Usage}
\begin{verbatim}
vennCounts(classification, include="both")
vennDiagram(object, include="both", names, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{classification}] classification matrix of 0's and 1's indicating significance of a test.
Usually created by \code{\Link{classifyTests}}.
\item[\code{object}] either a classification matrix or a \code{VennCounts} object produced by \code{vennCounts}.
\item[\code{include}] character string specifying whether to counts genes up-regulated, down-regulated or both.
Choices are \code{"both"}, \code{"up"} or \code{"down"}.
\item[\code{names}] optional character vector giving names for the sets or contrasts
\item[\code{...}] any other arguments are passed to \code{plot}
\end{ldescription}
\end{Arguments}
\begin{Value}
\code{vennCounts} produces a \code{VennCounts} object, which is a numeric matrix with last column \code{"Counts"} giving counts for each possible vector outcome.\end{Value}
\begin{Author}\relax
Gordon Smyth and James Wettenhall
\end{Author}
\begin{SeeAlso}\relax
An overview of linear model functions in limma is given by \link{5.LinearModels}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
tstat <- matrix(rt(300,df=10),100,3)
tstat[1:33,] <- tstat[1:33,]+2
clas <- classifyTests(tstat,df=10,p.value=0.05)
a <- vennCounts(clas)
print(a)
vennDiagram(a)
\end{ExampleCode}
\end{Examples}

