\HeaderA{normalize.quantiles.robust}{Robust Quantile Normalization}{normalize.quantiles.robust}
\aliasA{normalize.AffyBatch.quantiles.robust}{normalize.quantiles.robust}{normalize.AffyBatch.quantiles.robust}
\keyword{manip}{normalize.quantiles.robust}
\begin{Description}\relax
Using a normalization based upon quantiles, this function
normalizes a matrix of probe level intensities. Allows weighting of chips
\end{Description}
\begin{Usage}
\begin{verbatim}
    normalize.AffyBatch.quantiles.robust(abatch,
type=c("separate","pmonly","mmonly","together"),
weights=NULL,remove.extreme=c("variance","mean","both","none"),n.remove=1,use.median=FALSE,use.log2=FALSE)

\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{abatch}] An \code{\LinkA{AffyBatch}{AffyBatch}}
\item[\code{type}] A string specifying how the normalization should be
applied. See details for more.
\item[\code{weights}] A vector of weights, one for each chip
\item[\code{remove.extreme}] If weights is null, then this will be used for
determining which chips to remove from the calculation of the
normalization distribution, See details for more info
\item[\code{n.remove}] number of chips to remove
\item[\code{use.median}] if TRUE use the median to compute normalization
chip, otherwise uses a weighted mean
\item[\code{use.log2}] work on log2 scale. This means we will be using the
geometric mean rather than ordinary mean
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
This method is based upon the concept of a quantile-quantile 
plot extended to n dimensions. Note that the matrix is of intensities
not log intensities. The function performs better with raw
intensities.

Choosing \bold{variance} will remove chips with variances much higher
or lower than the other chips, \bold{mean} removes chips with the mean
most different from all the other means, \bold{both} removes first
extreme variance and then an extreme mean. The option \bold{none} does
not remove any chips, but will assign equal weights to all chips.

The type argument should be one of
\code{"separate","pmonly","mmonly","together"} which indicates whether
to normalize only one probe type (PM,MM) or both together or separately.
\end{Details}
\begin{Value}
a matrix of normalized intensites
\end{Value}
\begin{Note}\relax
This function is still experimental.
\end{Note}
\begin{Author}\relax
Ben Bolstad, \email{bmb@bmbolstad.com}
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{normalize}{normalize}}, \code{\LinkA{normalize.quantiles}{normalize.quantiles}}
\end{SeeAlso}

