\HeaderA{activeNet}{Functional classification of gene networks}{activeNet}
\keyword{methods}{activeNet}
\begin{Description}\relax
This function calculate a statistic for each gene network in each
biological condition that measure the profile of activation of the
network in that condition. Also the function measures the significance
of the results.
\end{Description}
\begin{Usage}
\begin{verbatim}
activeNet(data=NULL, samples=NULL, sLabelID="Classification",
          type="Rpearson", bRep=1000, alternative = "greater",
          adjP="none")
\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 networks stored in \code{Paths} slot.
\item[\code{sLabelID}] character string specifying identification of sample
label to be used. 
\item[\code{samples}] a list with character vectors specifying the groups
that must be compared.
\item[\code{type}] character string giving the type of correlation to be
calculated. May be 'Rpearson' (default), 'pearson', 'kendall',
'spearman' or 'MI'.
\item[\code{bRep}] integer number specifying the bootstraps to be done in the
correlation test.
\item[\code{alternative}] character string specifying the alternative
hypotheses. May be 'greater' (default) to test the activity of the
networks in accordance to the to the graph or 'less' to test the
activity of the network antagonic to the graph.
\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.
\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.maigesActNet}{plot.maigesActNet}} and
\code{\LinkA{image.maigesActNet}{image.maigesActNet}} methods to display the results of this
analysis.
\end{Details}
\begin{Value}
The result of this function is an object of class \code{\LinkA{maigesActNet}{maigesActNet}}.
\end{Value}
\begin{Author}\relax
Gustavo H. Esteves <\email{gesteves@vision.ime.usp.br}>
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{activeNetScoreHTML}{activeNetScoreHTML}}, \code{\LinkA{maigesActNet}{maigesActNet}},
\code{\LinkA{plot.maigesActNet}{plot.maigesActNet}}, \code{\LinkA{image.maigesActNet}{image.maigesActNet}}, \code{\LinkA{mt.rawp2adjp}{mt.rawp2adjp}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## Loading the dataset
data(gastro)

## Doing functional classification of gene networks for sample Label
## given by 'Tissue'
gastro.net = activeNet(gastro.summ, sLabelID="Tissue")
\end{ExampleCode}
\end{Examples}

