\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.quantiles.robust(x,weights=NULL,
                remove.extreme=c("variance","mean","both","none"),
                n.remove=1,approx.meth = FALSE,use.median=FALSE,use.log2=FALSE)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] A matrix of intensities, columns are chips, rows are probes
\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{approx.meth}] Use the approximation method. Not currently
implememnted
\item[\code{use.median}] if TRUE use the median to compute normalization
chip, otherwise use a weighted median
\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.
\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{bolstad@stat.berkeley.edu}
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{normalize}{normalize}}, \code{\LinkA{normalize.quantiles}{normalize.quantiles}}
\end{SeeAlso}

