\HeaderA{plot.qq}{Histogram and Normal Quantile-Quantile plot}{plot.qq}
\keyword{hplot}{plot.qq}
\begin{Description}\relax
Produces a histogram and a normal Quantile-Quantile plot
of the data. The points corresponding to genes with statistics
less/greater than a user defined threshold are highlighted. The
histogram and Q-Q plots are displayed on the same page.
\end{Description}
\begin{Usage}
\begin{verbatim}
plot.qq(x, name, low=-5, high=5,...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] a numeric vector containing the statistics whose histogram
and Q-Q plot will be produced. Missing values (NAs) are allowed.
\item[\code{name}] title for the plots.
\item[\code{low}] lower threshold: points with statistic < low are colored
in green.
\item[\code{high}] upper threshold: points with statistic > high are
colored in red.
\item[\code{...}] additional graphical parameters
\end{ldescription}
\end{Arguments}
\begin{Author}\relax
Sandrine Dudoit, \email{sandrine@stat.berkeley.edu} \\
Yee Hwa Yang, \email{yeehwa@stat.berkeley.edu}
\end{Author}
\begin{References}\relax
Chambers, J. M., Cleveland, W. S., Kleiner, B. and
Tukey, P. A. (1983). Graphical Methods for Data Analysis. Wadsworth,
Belmont, California. 

Hoaglin, D. C., Mosteller, F. and Tukey, J.  W., editors
(1983). Understanding Robust and Exploratory Data Analysis. Wiley,
New York.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{plot.spatial}{plot.spatial}}, \code{\LinkA{plot.t2}{plot.t2}},
\code{\LinkA{stat.t2}{stat.t2}}, \code{\LinkA{hist}{hist}}, \code{\LinkA{qqnorm}{qqnorm}}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(MouseArray)
## mouse.setup <- init.grid()
## mouse.data <- init.data() ## see \emph{init.data}
## mouse.lratio <- stat.ma(mouse.data, mouse.setup)

## Calculation of t-statistics
## cl <- c(rep(1,3), rep(2,3))
## mouse.t2 <- stat.t2(mouse.lratio, cl)

## Diagnostic plots
plot.qq(mouse.t2$t, "Mouse")
\end{ExampleCode}
\end{Examples}

