\HeaderA{deds.chooseTest}{Selection of the Most Common Statistics for Differential Expression}{deds.chooseTest}
\keyword{univar}{deds.chooseTest}
\begin{Description}\relax
This function selects a set of functions of common statistics for differential
expression in microarray data analysis, given specific observation
class labels. As a default, t-statistics, fold change and SAM are selected.
\end{Description}
\begin{Usage}
\begin{verbatim}
deds.chooseTest(L = NULL, tests = c("t", "sam", "fc"))
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{L}] A vector of integers corresponding to observation (column)
class labels. For \eqn{k}{} classes, the labels must be integers
between 0 and \eqn{k-1}{}.
\item[\code{tests}] A character vector specifying the statistics to be
used to test the null hypothesis of no association between the
variables and the class labels. For DEDS, there should be more than
one statistic chosen from the following:\\
\Tabular{ll}{
"t": & t-statistics; \\
"f": & F-statistics;\\
"fc":& fold changes;\\
"sam": & SAM-statistics; \\
"modt": & moderated t-statistics;\\
"modf": & moderated F-statistics; \\
"B": & B-statistics.}
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
\code{deds.chooseTest} can be used together with the function
\code{deds.stat}. The user specifies the types of statistics needed for
subsequent DEDS analysis by the argument \code{tests} and the function
returns accordingly a list the statistics function, which could be
used for input \code{testfun} in the function \code{deds.stat}.
\end{Details}
\begin{Value}
A list of statistics functions specified by the user which could be
used for input in the function \code{deds.stat}.
\end{Value}
\begin{Author}\relax
Yuanyuan Xiao, \email{yxiao@itsa.ucsf.edu}, \\
Jean Yee Hwa Yang, \email{jean@biostat.ucsf.edu}.
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{comp.t}{comp.t}}, \code{\LinkA{comp.FC}{comp.FC}}, \code{\LinkA{comp.SAM}{comp.SAM}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
X <- matrix(rnorm(1000,0,0.5), nc=10)
L <- rep(0:1,c(5,5))

# genes 1-10 are differentially expressed
X[1:10,6:10]<-X[1:10,6:10]+1

# as a default, chooses t, fc and sam
funcs <- deds.chooseTest(L)
deds.X <- deds.stat(X, L, testfun=funcs)

# chooses F statistic, SAM statistic, and moderated F statistic
L <- rep(0:2, c(3,3,4))
funcs <- deds.chooseTest(L, tests=c("f", "sam", "modf"))

\end{ExampleCode}
\end{Examples}

