\Header{generateExprVal}{Compute a summary expression value from the probes intensities}
\alias{express.summary.stat}{generateExprVal}
\alias{express.summary.stat-methods}{generateExprVal}
\alias{express.summary.stat.methods}{generateExprVal}
\alias{generateExprVal-methods}{generateExprVal}
\alias{generateExprVal.methods}{generateExprVal}
\begin{Description}\relax
Compute a summary expression value from the probes intensities
\end{Description}
\begin{Usage}
\begin{verbatim}
generateExprVal.methods # vector of names of methods

express.summary.stat(x, pmcorrect, summary, ...)
express.summary.stat.methods # vector of names of methods
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] a (\code{ProbeSet}
\item[\code{pmcorrect}] the method used to correct the PM values before
summarizing to an expression value.
\item[\code{summary}] the method used to generate the expression value.
\item[\code{...}] other parameters the method might need... (see the
corresponding methods below...)
\end{ldescription}
\end{Arguments}
\begin{Value}
Returns a vector of expression values.
\end{Value}
\begin{Examples}
\begin{ExampleCode}
data(affybatch.example)

p <- probeset(affybatch.example, "A28102_at")[[1]]

par(mfcol=c(5,2))
mymethods <- express.summary.stat.methods
nmet <- length(mymethods)
nc <- ncol(pm(p))

layout(matrix(c(1:nc, rep(nc+1, nc)), nc, 2), width = c(1, 1))

barplot(p)

results <- matrix(0, nc, nmet)
rownames(results) <- paste("sample", 1:nc)
colnames(results) <- mymethods

for (i in 1:nmet) {
  ev <- express.summary.stat(p, summary=mymethods[i], pmcorrect="pmonly")
  if (mymethods[[i]] != "medianpolish")
    results[, i] <- 2^(ev$exprs)
  else
    results[, i] <- ev$exprs
}

dotchart(results, labels=paste("sample", 1:nc))

\end{ExampleCode}
\end{Examples}

