%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % ./testOneGraph.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{testOneGraph} \alias{testOneGraph} \title{Applies a serie of two-sample tests to each connected component of a graph using various statistics} \description{ 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)} \arguments{ \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.} } \value{ 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} \seealso{ \code{\link{testOneConnectedComponent}}() } \examples{ library("KEGGgraph") data("Loi2008_DEGraphVignette") 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") print(pname) ## DEGraph T2 test resList <- testOneGraph(graph, exprData, classData, verbose=TRUE, prop=0.2) ## Largest connected component res <- resList[[1]] gr <- res$graph ## individual t statistics shift <- apply(exprData, 1, FUN=function(x) { tt <- t.test(x[classData==0], x[classData==1]) tt$statistic }) 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) title(pname) 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) } }