\HeaderA{stat.Newton}{Apply Newtons single slide method}{stat.Newton}
\keyword{models}{stat.Newton}
\begin{Description}\relax
Applies Newtons single slide method.
\end{Description}
\begin{Usage}
\begin{verbatim}
stat.Newton(RG,layout,norm="p", image.id=1,pout=TRUE)

\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{RG}] a list with 4 elements, each represents a matrix with p rows for p
genes and n columns for n slides. \\
The first element "R" contains the raw red intensities from slide
i=1,...,n .\\
Similarly, the second element "G" contains the raw green
intensities. \\
The third element "Rb"  contains the background red intensities and \\
the fourth element "Gb" contains the  background green intensities.\\
This list structure can be generated by the interactive function
\code{\LinkA{init.data}{init.data}}. 
\item[\code{layout}] a list specifying the dimensions of the spot matrix and the grid
matrix.  This can be generated by calling \code{\LinkA{init.grid}{init.grid}}.
\item[\code{norm}] Character string, one of "n", "m", "l", "p" or "s".  This
argument specifies the type of normalization method to be performed:
"n" no normalization between the 2 channels; "m"
\code{\LinkA{median}{median}} normalization, which sets the median of log
intensity ratios to zero; "l" global \code{\LinkA{lowess}{lowess}}
normalization; "p" print-tip group lowess normalization and "s"
scaled print-tip group lowess normalization. The default method is
set to print-tip normalization.
\item[\code{image.id}] Specifies image to which Chen's method will be applied.
\item[\code{pout}] if TRUE, an M vs. A plot will be produced with limits due
to Newton, Specifically limits at the 1:1, 1:10 and 1:100 log odds ratio. If FALSE, return a list with pertinant information
\end{ldescription}
\end{Arguments}
\begin{Value}
List containing the following components:

\begin{ldescription}
\item[\code{theta}] parameters estimated by EM algorithm
\item[\code{lod}] Log odds ratio of being differentially expressed for each gene
\end{ldescription}
\end{Value}
\begin{Author}\relax
Ben Bolstad, \email{bolstad@stat.berkeley.edu}
\end{Author}
\begin{References}\relax
Newton, M.N., C.M. Kendziorski, C.S. Richmond, F.R. Blattner, and
K.W. Tsui . On differential variability of expression ratios:
Improving statistical inference about gene expression changes from
microarray data. Technical Report 139, Department of Biostatistics and
Medical Informatics, UW Madison, 1999. \url{http://www.stat.wisc.edu/~newton/papers/abstracts/btr139a.html}
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{stat.Chen}{stat.Chen}},\code{\LinkA{stat.ChurSap}{stat.ChurSap}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(MouseArray)
##mouse.setup <- init.grid() 
##mouse.data <- init.data() ## see \emph{init.data}
stat.Newton(mouse.data,mouse.setup,image.id=3)
\end{ExampleCode}
\end{Examples}

