\HeaderA{proboStruct-class}{Class "proboStruct"}{proboStruct.Rdash.class}
\keyword{classes}{proboStruct-class}
\begin{Description}\relax
structure for managing proboscis plot data
\end{Description}
\begin{Section}{Objects from the Class}
Objects can be created by calls of the form \code{new("proboStruct", ...)}.
\end{Section}
\begin{Section}{Slots}
\describe{
\item[\code{.Data}:] Object of class \code{"list"} ~~ 
\item[\code{call}:] Object of class \code{"call"} ~~ 
}
\end{Section}
\begin{Section}{Extends}
Class \code{"\LinkA{list}{list.Rdash.class}"}, from data part.
Class \code{"\LinkA{vector}{vector.Rdash.class}"}, by class "list", distance 2.
Class \code{"\LinkA{AssayData}{AssayData.Rdash.class}"}, by class "list", distance 2.
\end{Section}
\begin{Section}{Methods}
plot
\end{Section}
\begin{Note}\relax
The proboscis plot shows how the 
probability of self-consistent monotone titration  (SCMT)
varies with the spiked difference in concentrations of
two mRNA preparations in an MAQC dataset.
\end{Note}
\begin{Author}\relax
V Carey <stvjc@channing.harvard.edu>
\end{Author}
\begin{References}\relax
For Figure 2 of Shippy et al., Using RNA sample titrations... (Nat Biotech,
24(9):1123-1131, Sep 2006)
\end{References}
\begin{Examples}
\begin{ExampleCode}
data(afxsubRMAES)
NN1 = proboscis(afxsubRMAES)
plot(NN1)
showClass("proboStruct")
\end{ExampleCode}
\end{Examples}

