\HeaderA{pamr.batchadjust}{A function to mean-adjust microarray data by batches}{pamr.batchadjust}
\begin{Description}\relax
A function to mean-adjust microarray data by batches
\end{Description}
\begin{Usage}
\begin{verbatim}
pamr.batchadjust(data)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{data}] The input data. A list with components: x- an expression
genes in the rows, samples in the columns, and y-  a vector of
the class labels for each sample, and batchlabels- a vector of batch
labels for each sample.
\end{ldescription}

This object if the same form as that produced by pamr.from.excel.
\end{Arguments}
\begin{Details}\relax
\code{pamr.batchadjust} 
does a genewise one-way ANOVA adjustment for expression values.
Let x(i,j) be the expression for gene i in sample j.
Suppose sample j in in batch b, and let B be the set of all samples
in batch b. Then \code{pamr.batchadjust}  adjusts  x(i,j) to
x(i,j) - mean[x(i,j)]  where the mean is taken over all samples j in B
\end{Details}
\begin{Value}
A data object  of the same form as the input data, with x
replaced by the adjusted x
\end{Value}
\begin{Author}\relax
Trevor Hastie,Robert Tibshirani, Balasubramanian Narasimhan, and Gilbert Chu
\end{Author}
\begin{References}\relax
\end{References}
\begin{Examples}
\begin{ExampleCode}
set.seed(120)
#generate some data
x <- matrix(rnorm(1000*20),ncol=20)
y <- sample(c(1:4),size=20,replace=TRUE)
batchlabels <- sample(c(1:5),size=20,replace=TRUE)
mydata <- list(x=x,y=factor(y),batchlabels=factor(batchlabels))

mydata2 <- pamr.batchadjust(mydata)
\end{ExampleCode}
\end{Examples}

