\HeaderA{plot.bayesian}{Plots lodscore vs effect estimate (the output of stat.bayesian() or stat.bay.est()).}{plot.bayesian}
\keyword{hplot}{plot.bayesian}
\begin{Description}\relax
This function plots the results of stat.bayesian() or stat.bay.est()
highlighting genes meeting userspecified criteria.
\end{Description}
\begin{Usage}
\begin{verbatim}
plot.bayesian(x=NULL, Mbar=x$Xprep$Mbar, lods=x$lods, 
type="t", spec=50, ch=NULL, col="black",...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] output from stat.bayesian() or stat.bay.est()
\item[\code{Mbar}] Effect estimate for each gene.
\item[\code{lods}] Posterior lodsratio for each gene.
\item[\code{type}] Type of criteria for highlighting genes (see details).
\item[\code{spec}] Specifies cutoff etc. depending on \code{type}.
\item[\code{ch}] Character with which to selected highlight genes. (Default
is the gene index.)
\item[\code{col}] Colour of highlighted genes. (Default is black.)
\item[\code{...}] Additional graphical parameters
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
If type='t', plot.bayesian() highlights the top spec genes.
If type='c', plot.bayesian() highlights the genes with lods>=spec.
If type='i', plot.bayesian() highlights the genes with indecies
specified in spec.
\end{Details}
\begin{Author}\relax
Ingrid Lönnstedt \email{ingrid@math.uu.se} \\
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{stat.bayesian}{stat.bayesian}},\code{\LinkA{stat.bay.est}{stat.bay.est}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(MouseArray)
## mouse.setup <- init.grid() 
## mouse.data <- init.data() ## see \emph{init.data} 
## mouse.lratio <- stat.ma(mouse.data, mouse.setup)
mouse.bayesian<-stat.bayesian(M=mouse.lratio$M)

plot.bayesian(mouse.bayesian)
plot.bayesian(mouse.bayesian,type='c',spec=0,col='blue')
plot.bayesian(mouse.bayesian,type='i',spec=c(1000,2000),col='green')
plot.bayesian(mouse.bayesian,type='i',spec=1:length(mouse.bayesian$lods))

\end{ExampleCode}
\end{Examples}

