\HeaderA{plot.confband.points}{Highlights a Set of Points on the Current M vs A Plot}{plot.confband.points}
\keyword{aplot}{plot.confband.points}
\begin{Description}\relax
This function highlights a prespecified proportion of extreme points
on the M vs A plots.
\end{Description}
\begin{Usage}
\begin{verbatim}
plot.confband.points(x, M, crit1=0.025, crit2=crit1, nclass=10, col.ex, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] a vector giving the x-coordinates of the points in the scatter
plot. In the microarray context, this could be a vector of
average log intensities. ie A
\item[\code{M}] a vector giving the y-coordinates of the points in the scatter
plot. In the microarray context, this could be a vector of log
intensity ratios.
\item[\code{crit1}] The number of points to be highlighted on the M vs A plot.
If crit1 < 1, the crit1*100\% spots with the smallest M values
will be highlighted. If crit1 >= 1, the crit spots with the
smallest M values are highlighted.
\item[\code{crit2}] Similar to "crit1".   If crit2 < 1, the crit2*100\%
spots with the largest M values will be highlighted. If crit2 >= 1,
the crit2 spots with the smallest M values are highlighted.
\item[\code{nclass}] A single number giving the approximate number of
intensity depedent groups to consider.
\item[\code{col.ex}] A color for extreme points
\item[\code{...}] graphical parameters may also be supplied as arguments
to the function (see \code{\LinkA{par}{par}}).
\end{ldescription}
\end{Arguments}
\begin{Value}
Points are added to the current plot.
\end{Value}
\begin{Note}\relax
An M vs A plot must be constructed \bold{prior} to the
execution of this function.
\end{Note}
\begin{SeeAlso}\relax
\code{\LinkA{plot.mva}{plot.mva}}, \code{\LinkA{stat.ma}{stat.ma}},
\code{\LinkA{lines}{lines}}, \code{\LinkA{matlines}{matlines}},
\code{\LinkA{plot.confband.text}{plot.confband.text}}, \code{\LinkA{plot.confband.lines}{plot.confband.lines}} .
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}data(MouseArray)
## mouse.setup <- init.grid()
## mouse.data <- init.data()

plot.mva(mouse.data, mouse.setup) ## an M vs A plot 

mouse.lratio <- stat.ma(mouse.data, mouse.setup)

plot.confband.points(mouse.lratio$A, mouse.lratio$M)

## 2.5% of the spots with the smallest and largest M values are
## highlighted on the M vs A plot. 
\end{ExampleCode}
\end{Examples}

