% Do not modify this file since it was automatically generated from:
%  ./testOneGraph.R
% by the Rdoc compiler part of the R.oo package.


\title{Applies a serie of two-sample tests to each connected component
  of a graph using various statistics}

 Applies a serie of two-sample tests to each connected component
  of a graph using various statistics.

\usage{testOneGraph(graph, data, classes, useInteractionSigns=TRUE, ..., verbose=FALSE)}

  \item{graph}{A \code{\link[=graph-class]{graph}} object.}
  \item{data}{A 'matrix' (size: number 'p' of genes x number 'n' of samples) of gene expression.}
  \item{classes}{A 'vector' (length: 'n') of class assignments.}
  \item{useInteractionSigns}{A \code{\link[base]{logical}} value indicating whether the sign of interaction should be taken into account.}
  \item{...}{Further arguments to be passed to testOneConnectedComponent.}
  \item{verbose}{If \code{\link[base:logical]{TRUE}}, extra information is output.}

 A structured \code{\link[base]{list}} containing the p-values of the tests, the
 \code{\link[=graph-class]{graph}} object of the connected component and the number of
 retained Fourier dimensions.

\author{Laurent Jacob, Pierre Neuvial and Sandrine Dudoit}


## library("NCIgraph")

exprData <- exprLoi2008
classData <- classLoi2008
annData <- annLoi2008

rn <- rownames(exprData)

## Retrieve expression levels data for genes from one KEGG pathway
graph <- grListKEGG[[1]]
pname <- attr(graph, "label")

## DEGraph T2 test
resList <- testOneGraph(graph, exprData, classData, verbose=TRUE, prop=0.2)

## Largest connected component
res <- resList[[1]]
gr <- res$graph

## individual t statistics
shift <- apply(exprData, 1, FUN=function(x) {
  tt <- t.test(x[classData==0], x[classData==1])
names(shift) <- translateGeneID2KEGGID(names(shift))

## color palette
if (require(marray)) {
  pal <- maPalette(low="red", high="green", mid="black", k=100)
} else {
  pal <- heat.colors(100)

## plot results
dn <- getDisplayName(gr, shortLabel=TRUE)
mm <- match(translateKEGGID2GeneID(nodes(gr)), rownames(annData))
dn <- annData[mm, "NCBI.gene.symbol"]
pvg <- plotValuedGraph(gr, values=shift, nodeLabels=dn, qMax=0.95, colorPalette=pal, height=40, lwd=1, verbose=TRUE, cex=0.5)

txt1 <- sprintf("p(T2)=\%s", signif(res$p.value[1], 2))
txt2 <- sprintf("p(T2F[\%s])=\%s", res$k, signif(res$p.value[2]))
txt <- paste(txt1, txt2, sep="\n")
stext(side=3, pos=1, txt)
if (require(fields)) {
  image.plot(legend.only=TRUE, zlim=range(pvg$breaks), col=pal, legend.shrink=0.3, legend.width=0.8, legend.lab="t-scores", legend.mar=3.3)