\name{pretty.dend}
\alias{pretty.dend}
\title{Draw hierarchical tree of gene expression data with a colorbar for numerous class vectors}
\description{
Function which performs a hierarchical cluster analysis of data, drawing a dendrogram, with colorbars for different sample covariate beneath the dendrogram}

\usage{pretty.dend(dataset, labels = NULL, title = "", classvec = NULL,covars=1,returnTree=FALSE, \dots)
}
\arguments{
  \item{dataset}{ a \code{\link{matrix}}, \code{\link{data.frame}}, 
    \code{\link[Biobase:ExpressionSet-class]{ExpressionSet}} or
    \code{\link[marrayClasses:marrayRaw-class]{marrayRaw}}.  
     If the input is gene expression data in a \code{\link{matrix}} or \code{\link{data.frame}}. The 
     rows and columns are expected to contain the variables (genes) and cases (array samples) 
     respectively.}
  \item{labels}{Vector, labels to be placed on samples in plots. Default is rownames(dataset).}
  \item{title}{Character, label to be placed on plots. Default is \code{NULL}.}
  \item{classvec}{ A \code{factor} or \code{vector} or \code{matrix} or \code{data.frame} which describes the classes in columns of the \code{dataset}.  Default is \code{NULL}.}
  \item{covars}{ Numeric. The columns of the data.frame classve to be used as class vectors.  These will be displayed as color bars under the dendrogram. The default is 1 (column 1).}
  \item{returnTree}{ Logical. Return the hieracrhical cluster analysis results. Default is \code{FALSE}.}
  \item{\dots}{further arguments passed to or from other methods.}
  }
\details{The hierarchical plot is produced using average linkage cluster analysis with 1- Pearson's correlation metric.}
\value{}
\references{  }
\author{Aedin Culhane}
\note{}
\seealso{ See also as \code{\link[overview]{overview}}, \code{\link[hclust]{hclust}}}
\examples{
  data(khan)
  logkhan<-log2(khan$train)
  pretty.dend(logkhan, classvec=khan$train.classes, labels=khan$train.classes)
 
 # Get a character vector which defines which khan samples are cell lines or tissue sample
  cellType = cellType=sapply((strsplit(colnames(khan$train), "\\.")), function(x) substr(x[[2]],1,1))
  khanAnnot= cbind(as.character(khan$train.classes),cellType)
  print(khanAnnot[1:3,])

# Add 2 color bar, one for cancer subtype, another for cell type under dendrogram
  pretty.dend(logkhan, classvec=khanAnnot, covars = c(1,2), labels=khan$train.classes)
}
\keyword{hplot}% at least one, from doc/KEYWORDS
\keyword{manip}% __ONLY ONE__ keyword per line