\HeaderA{dstar}{Tools for Meta-analysis of gene expression data.}{dstar}
\aliasA{getdF}{dstar}{getdF}
\aliasA{getdF,exprSet,numeric-method}{dstar}{getdF,exprSet,numeric.Rdash.method}
\aliasA{getdF,matrix,numeric-method}{dstar}{getdF,matrix,numeric.Rdash.method}
\aliasA{sigmad}{dstar}{sigmad}
\keyword{htest}{dstar}
\begin{Description}\relax
A small number of meta-analysis functions for comparing two
gene expression experiments are provided.
\end{Description}
\begin{Usage}
\begin{verbatim}
dstar(d, n)
getdF(data, categ)
sigmad(d, ng1, ng2)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{d}] A vector of t-statistics, ie. the output of \code{getdF}.
\item[\code{n}] The number of t-statistics. 
\item[\code{data}] The data used to compute t-statistics, either a matrix or
an \code{exprSet}
\item[\code{categ}] A vector of 0's and 1's indicating group membership.
\item[\code{ng1}] The number of samples in group 1.
\item[\code{ng2}] The number of samples in group 2.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
The functions \code{getdF} compute t-test statistics
for the input data and group membership (note that group membership
must be indicated by a vector of 0's and 1's).

The function \code{dstar} computes an unbiased estimate of the t-test.
The function \code{sigmad} computes the variance estimate of
\code{dstar}.
\end{Details}
\begin{Value}
The different functions have different return values, but generally
they are vectors of the requested quantities.
\end{Value}
\begin{Author}\relax
L. Lusa, R. Gray and R. Gentleman
\end{Author}
\begin{References}\relax
Choi et al, Combining multiple microarray studies and
modeling interstudy variation. Bioinformatics, 2003, i84-i90.
\end{References}
\begin{Examples}
\begin{ExampleCode}
  
  x = matrix(rnorm(1000), nc=10)
  ds = getdF(x, rep(c(0,1), c(5,5)))
  dst = dstar(ds, ncol(x))
  sgd = sigmad(ds, 5, 5)

\end{ExampleCode}
\end{Examples}

