\HeaderA{plot.pairwise.comparison}{Plots a PairComp object}{plot.pairwise.comparison}
\aliasA{plot,PairComp}{plot.pairwise.comparison}{plot,PairComp}
\aliasA{plot,PairComp-method}{plot.pairwise.comparison}{plot,PairComp.Rdash.method}
\keyword{misc}{plot.pairwise.comparison}
\begin{Description}\relax
Draws a scatter plot between means from a pairwise comparison. Colours according to PMA calls and identifies 'signficant' genes yielded by a filtering
\end{Description}
\begin{Usage}
\begin{verbatim}
plot.pairwise.comparison(x,y=NULL,labels=colnames(means(x)),showPMA=TRUE,type="scatter",...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] A \code{PairComp} object 
\item[\code{y}] A \code{PairComp} object 
\item[\code{labels}] A list containing x and y axis labels 
\item[\code{showPMA}] True if PMA calls are to be identified 
\item[\code{type}] Can be 'scatter', 'ma' or 'volcano' 
\item[\code{...}] Additional arguments to plot 
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
Takes a PairComp object (as produced by \code{pairwise.comparison}
and plots a scatter plot between the sample means. If PMA calls are
present in the \code{calls} slot of the object then it uses them to
colour the points. Present on all arrays: red; absent on all arrays:
yellow; present in all some arrays; orange. In
addition, if a second \code{PairComp} object is supplied, it
identifies spots in that object, by drawing them as black
circles. This allows, for example, the results of a
\code{pairwise.filter} to be plotted on the same graph.

If type is 'scatter' does a simple scatter plot.
If type is 'volcano' does a volcano plot.
If type is 'ma' does an MA plot.
\end{Details}
\begin{Author}\relax
Crispin J Miller
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{pairwise.comparison}{pairwise.comparison}} \code{\LinkA{pairwise.filter}{pairwise.filter}} \code{\LinkA{trad.scatter.plot}{trad.scatter.plot}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
  ## Not run: 
    pc <- pairwise.comparison(eset.mas,group="group",members=c("a","b"),spots=eset)
    pf <- pairwise.filter(pc)
    plot(pc,pf)
  
## End(Not run)
\end{ExampleCode}
\end{Examples}