Revision b7c0afd9fdb886458ef54c202368a21551f6b1b6 authored by Max Kuhn on 11 June 2008, 14:44:07 UTC, committed by cran-robot on 11 June 2008, 14:44:07 UTC
1 parent 6a94bf7
normalize.AffyBatch.normalize2Reference.Rd
\name{normalize.AffyBatch.normalize2Reference}
\alias{normalize.AffyBatch.normalize2Reference}
\title{Quantile Normalization to a Reference Distribution}
\description{
Quantile normalization based upon a reference distribution. This function
normalizes a matrix of data (typically Affy probe level intensities).
}
\usage{
normalize.AffyBatch.normalize2Reference(
abatch,
type = c("separate", "pmonly", "mmonly", "together"),
ref = NULL)
}
\arguments{
\item{abatch}{An \code{{AffyBatch}}}
\item{type}{A string specifying how the normalization should be
applied. See details for more.}
\item{ref}{A vector of reference values. See details for more.}
}
\details{This method is based upon the concept of a quantile-quantile
plot extended to n dimensions. No special allowances are made for
outliers. If you make use of quantile normalization either through
\code{rma} or \code{expresso}
please cite Bolstad et al, Bioinformatics (2003).
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.
The function uses the data supplied in \code{ref} to use as the reference
distribution. In other words, the PMs in \code{abatch} will be normalized
to have the same distribution as the data in \code{ref}. If \code{ref} is
\code{NULL}, the normalizing takes place using the average quantiles
of the PM values in \code{abatch} (just as in \code{normalize.AffyBatch.quantile}).
}
\value{
A normalized \code{AffyBatch}.
}
\references{
Bolstad, B (2001) \emph{Probe Level Quantile Normalization of High Density
Oligonucleotide Array Data}. Unpublished manuscript
Bolstad, B. M., Irizarry R. A., Astrand, M, and Speed, T. P. (2003)
\emph{A Comparison of Normalization Methods for High Density
Oligonucleotide Array Data Based on Bias and Variance.}
Bioinformatics 19(2) ,pp 185-193.
}
\author{Max Kuhn, adapted from Ben Bolstad, \email{bolstad@stat.berkeley.edu}}
\seealso{\code{normalize}}
\examples{
# first, let affy/expresso know that the method exists
# normalize.AffyBatch.methods <- c(normalize.AffyBatch.methods, "normalize2Reference")
# example not run, as it would take a while
# RawData <- ReadAffy(celfile.path=FilePath)
# Batch1Step1 <- bg.correct(RawData, "rma")
# Batch1Step2 <- normalize.AffyBatch.quantiles(Batch1Step1)
# referencePM <- pm(Batch1Step2)[,1]
# Batch1Step3 <- computeExprSet(Batch1Step2, "pmonly", "medianpolish")
# Batch2Step1 <- bg.correct(RawData2, "rma")
# Batch2Step2 <- normalize.AffyBatch.normalize2Reference(Batch2Step1, ref = referencePM)
# Batch2Step3 <- computeExprSet(Batch2Step2, "pmonly", "medianpolish")
}
\keyword{manip}
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