\name{r2xcluster} \alias{r2xcluster} \title{Write to Xcluster file format} \description{Converting data to Xcluster format} \usage{ r2xcluster(data,labels=FALSE,description=FALSE,file="xcluster.txt") } \arguments{ \item{file}{the path of the file} \item{data}{a matrix (or data frame) which provides the data to put into the file} \item{labels}{a logical value indicating whether we use the frist column as labels (NAME column for xcluster file)} \item{description}{a logical value indicating whether we use the second column as description (DESCRIPTION column for cluster file)} } \note{ \emph{Xcluster} is a C program made by \emph{Gavin Sherlock} that performs hierarchical clustering, K-means and SOM. \emph{Xcluster} is copyrighted. To get or have information about \emph{Xcluster}: \url{http://genome-www.stanford.edu/~sherlock/cluster.html} } \details{ Software \emph{Xcluster}, made by \emph{G. Sherlock} needs formatted input data like: \preformatted{ NAME DESCRIPTION GWEIGHT V2 V3 V4 EWEIGHT 1 1 1 gbk01 Gene1 1 0.9 0.4 1.4 gbk02 Gene2 1 0.6 0.2 0.2 gbk03 Gene3 1 1.6 1.1 0.9 gbk04 Gene4 1 0.4 1 1 } Line begining with \code{EWEIGHT} gives weights for each column (variable). Column \code{GWEIGHT} gives weights for each line (individuals). } \references{ Antoine Lucas and Sylvain Jasson, \emph{Using amap and ctc Packages for Huge Clustering}, R News, 2006, vol 6, issue 5 pages 58-60. } \examples{ ## Create data set.seed(1) m <- matrix(rep(1,3*24),ncol=3) m[9:16,3] <- 3 ; m[17:24,] <- 3 #create 3 groups m <- m+rnorm(24*3,0,0.5) #add noise m <- floor(10*m)/10 #just one digits r2xcluster(m) ## And once you have Xcluster program: \dontrun{ system('Xcluster -f xcluster.txt -e 0 -p 0 -s 0 -l 0') h <- xcluster2r('xcluster.gtr') plot(h,hang=-1) } } \keyword{file} \author{Antoine Lucas, \url{http://antoinelucas.free.fr/ctc}} \seealso{\code{\link{xcluster}}, \code{\link{xcluster2r}}, \code{\link[stats]{hclust}}, \code{\link[amap]{hcluster}}}