\HeaderA{mulTestCor}{Multiple testing corrections for package Envisage}{mulTestCor}
\keyword{models}{mulTestCor}
\begin{Description}\relax
This function corrects the p-values obtained from package
\pkg{Envisage} to account for problems with multiple testing. These
corrected p-values give a measure of the significance of model terms
on the effects on gene expression changes for individual genes.
\end{Description}
\begin{Usage}
\begin{verbatim}
  mulTestCor(pValues, MTC, pData, exprData, param4INT) 
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{pValues}] An object of class \code{data.frame} containing the
p-values from the Type II sum of squares analysis for each model
term for each gene.
\item[\code{MTC}] A character string that defines which multiple testing 
correction method to use (if any).  Available methods are
\code{None}, \code{BH}, \code{BY}, \code{Bonferroni}, \code{Holm},
\code{Hochberg}, \code{SidakSS}, \code{SidakSD}. More information on
these can be found in the package vignette. \code{BH} is selected by
default.
\item[\code{pData}] An object of class
\code{\LinkA{phenoData}{phenoData}} containing the
phenotypic information for the experiment.
\item[\code{exprData}] A matrix of expression values for each gene for each
sample. Usually calculated using \code{\LinkA{exprs}{exprs}} on an
object of class
\code{\LinkA{ExpressionSet}{ExpressionSet}}.
\item[\code{param4INT}] Character vector of variables for which interaction
terms should be calculated.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
The \pkg{Envisage} package contains methods allowing the use of 
linear models (LMs) for analysing significantly changing genes in 
experiments with a variety of sources of variation, be they
experimentally controlled variables such as drug treatment or time, or
non-controlled sources of confounding variation such as phenotypic or
environmental differences. This allows all sources of variation to be
considered when analysing for significant differential expression,
ensuring resulting genes are biologically relevent to the experimental
question. 

Due to the large number of genes analysed, gene expression analyses
can suffer from problems due to multiple hypothesis testing. The
function \code{\LinkA{mulTestCor}{mulTestCor}} performs the selected
multiple testing correction on the p-values indicating significance of
each model term for each gene in the analysis. 

\code{\LinkA{mulTestCor}{mulTestCor}} is an internal function and is not
designed to be accessed by users.
\end{Details}
\begin{Value}
An object of class \code{data.frame} is returned containing the
adjusted p-values for each model term for each gene.
\end{Value}
\begin{Author}\relax
Sam Robson \email{S.C.Robson@warwick.ac.uk}
\end{Author}
\begin{References}\relax
Robson, S. C., Hunter, E., Bird, H., Turner, H. (2008) 
\emph{Envisage: model-based significance analysis of microarray gene
expression data}, manuscript in preparation
\end{References}
\begin{SeeAlso}\relax
For the main \pkg{Envisage} method, see
\code{\LinkA{envisage}{envisage}}.
\end{SeeAlso}

