\name{hierM} \alias{hierM} \title{ Function to do hierarchical cluster analysis } \description{ This is a function to do hierarchical clustering analysis for objects of classes \code{\link{maiges}}, \code{\link{maigesRaw}} and \code{\link{maigesANOVA}}. Use the function \code{\link{hierMde}} for objects of class \code{\link{maigesDEcluster}}. } \usage{ hierM(data, group=c("C", "R", "B")[1], distance="correlation", method="complete", doHeat=TRUE, sLabelID="SAMPLE", gLabelID="GeneName", rmGenes=NULL, rmSamples=NULL, rmBad=TRUE, geneGrp=NULL, path=NULL, \dots) } \arguments{ \item{data}{object of class \code{\link{maigesRaw}}, \code{\link{maiges}}, \code{\link{maigesANOVA}} or \code{\link{maigesDEcluster}}.} \item{group}{character string giving the type of grouping: by rows 'R', columns 'C' (default) or both 'B'.} \item{distance}{char string giving the type of distance to use. Here we use the function \code{\link[amap:dist]{Dist}} and the possible values are 'euclidean', 'maximum', 'manhattan', 'canberra', 'binary', 'pearson', 'correlation' (default) and 'spearman'.} \item{method}{char string specifying the linkage method for the hierarchical cluster. Possible values are 'ward', 'single', 'complete' (default), 'average', 'mcquitty', 'median' or 'centroid'} \item{doHeat}{logical indicating to do or not the heatmap. If FALSE, only the dendrogram is displayed.} \item{sLabelID}{character string specifying the sample label ID to be used to label the samples.} \item{gLabelID}{character string specifying the gene label ID to be used to label the genes.} \item{rmGenes}{char list specifying genes to be removed.} \item{rmSamples}{char list specifying samples to be removed.} \item{rmBad}{logical indicating to remove or not bad spots (slot \code{BadSpots} in objects of class \code{\link{maiges}}, \code{\link{maigesRaw}} or \code{\link{maigesANOVA}}).} \item{geneGrp}{numerical or character specifying the gene group to be clustered. This is given by the columns of the slot \code{GeneGrps} in objects of classes \code{\link{maiges}}, \code{\link{maigesRaw}} and \code{\link{maigesANOVA}}.} \item{path}{numerical or character specifying the gene network to be clustered. This is given by the items of the slot \code{Paths} in objects of classes \code{\link{maiges}}, \code{\link{maigesRaw}} and \code{\link{maigesANOVA}}.} \item{\dots}{additional parameters for \code{\link[stats]{heatmap}} function.} } \details{ This function implements the hierarchical clustering method for objects of microarray data defined in this package. The default function for hierarchical clustering is the \code{\link[stats]{hclust}}. } \value{ This function display the heatmaps and don't return any object or value. } \seealso{ \code{\link{somM}} and \code{\link{kmeansM}} for displaying SOM and k-means clusters, respectively. } \examples{ ## Loading the dataset data(gastro) ## Doing a hierarchical cluster using all genes, for maigesRaw class hierM(gastro.raw, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"), sLabelID="Sample", gLabelID="Name", doHeat=FALSE) ## Doing a hierarchical cluster using all genes, for maigesNorm class hierM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"), sLabelID="Sample", gLabelID="Name", doHeat=FALSE) ## If you want to show the heatmap do hierM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"), sLabelID="Sample", gLabelID="Name", doHeat=TRUE) ## If you want to show the hierarchical branch in both margins do hierM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"), sLabelID="Sample", gLabelID="Name", doHeat=TRUE, group="B") ## If you want to use euclidean distance only into rows (spots or genes) hierM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"), sLabelID="Sample", gLabelID="Name", doHeat=FALSE, group="R", distance="euclidean") } \author{ Gustavo H. Esteves <\email{gesteves@vision.ime.usp.br}> } \keyword{hplot}