\HeaderA{activeMod}{Functional classification of gene groups}{activeMod}
\keyword{methods}{activeMod}
\begin{Description}\relax
This function calculate profiles of expression for groups of genes in
each sample of the dataset and for each biological condition (group of
samples).
\end{Description}
\begin{Usage}
\begin{verbatim}
activeMod(data=NULL, gNameID="GeneName", samples=NULL, usePaths=FALSE,
          sLabelID="Classification", adjP="none", cutExp=1,
          cutPhiper=0.05)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{data}] object of class \code{\LinkA{maiges}{maiges}} to be used to
functionally classify gene groups stored in \code{GeneGrps} slot.
\item[\code{gNameID}] character string specifying identification of gene
label to be used. 
\item[\code{sLabelID}] idem to the previous argument for identification of
sample label.
\item[\code{samples}] a list with character vectors specifying the groups
that must be compared.
\item[\code{usePaths}] logical specifying if the pathways given in
\code{Paths} slot must also be used, defaults to FALSE.
\item[\code{cutExp}] real number specifying the cutoff for expression levels
(to discretise the expression)
\item[\code{adjP}] character string giving the type of p-value
adjustment. May be 'Bonferroni', 'Holm', 'Hochberg', 'SidakSS',
'SidakSD', 'BH', 'BY' or 'none'. Defaults to 'none'. See function
\code{\LinkA{mt.rawp2adjp}{mt.rawp2adjp}} in package multtest for more details.
\item[\code{cutPhiper}] p-value cutoff to select significant gene groups.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
If the argument \code{samples} is NULL, all types defined by the
sample label given by \code{sLabelID} are used. It is possible to use
the \code{\LinkA{plot.maigesActMod}{plot.maigesActMod}} and
\code{\LinkA{image.maigesActMod}{image.maigesActMod}} to display the results of this
analysis. This function is based in the method proposed by
Segal et al. (2004).
\end{Details}
\begin{Value}
The result of this function is an object of class \code{\LinkA{maigesActMod}{maigesActMod}}.
\end{Value}
\begin{Author}\relax
Gustavo H. Esteves <\email{gesteves@vision.ime.usp.br}>
\end{Author}
\begin{References}\relax
Segal, E.; Friedman, N.; Koller, D. and Regev, A. A module map showing
conditional activity of expression modules in cancer. \bold{Nature
Genetics}, 36, 1090-1098, 2004. (\url{http://www.nature.com/ng/journal/v36/n10/abs/ng1434.html})
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{activeModScoreHTML}{activeModScoreHTML}}, \code{\LinkA{maigesActMod}{maigesActMod}},
\code{\LinkA{plot.maigesActMod}{plot.maigesActMod}}, \code{\LinkA{image.maigesActMod}{image.maigesActMod}}, \code{\LinkA{mt.rawp2adjp}{mt.rawp2adjp}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## Loading a little dataset
data(gastro)

## Doing functional classification of gene groups for 'Tissue' sample label
gastro.mod = activeMod(gastro.summ, sLabelID="Tissue", cutExp=1,
  cutPhiper=0.05)

## Doing functional classification of gene groups together with the
## networks given by Paths slot for 'Tissue' sample label. Also we are
## using a cuttoff for p-value of hipergeometric test as 0.1
gastro.mod = activeMod(gastro.summ, sLabelID="Tissue", cutExp=1,
  cutPhiper=0.1, usePaths=TRUE)
\end{ExampleCode}
\end{Examples}

