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r2cdt <- function(hr,hc,data,labels=FALSE,description=FALSE,file="cluster.cdt",dec="."){
#-------------------------------------------------------
#
# Created : 20/11/02
# Last Modified : Time-stamp: <2003-07-22 16:52:28 lucas>
#
# Description : Write data object to cdt
# file (Xcluster or Cluster output).
# Should be use with r2gtr
# Visualisation of cluster can be
# done with tools like treeview
#
# Author : Antoine Lucas
# lucas@toulouse.inra.fr
#
# Licence : GPL (r2xcluster, not Xcluster)
#
#-------------------------------------------------------
#
#
n <- dim(data)[1]
# Add GWEIGHT column
data <- as.data.frame(cbind(1,data))
# If the name column does not exist -> creation
# of this column else: put column name on
# first place. (column NAME in the file)
if(!description){
if(!labels){
data <- cbind(row.names(data),data)
}
else{
data <- cbind(as.factor(data[,2]),data)
}
}
else{
data <- cbind(as.factor(data[,3]),data[,-3])
}
# column YORF in the file
if(!labels){
data <- cbind(row.names(data),data)
}
else{
data <- cbind(as.factor(data[,3]),data[,-3])
}
# add GID column
GID <- paste ('GENE',0:(n-1),'X',sep='')
data <- cbind(as.factor(GID),data)
# Put data in right order
data <- data [hr$order,]
m <- dim(data)[2]
data[,5:m] <- data[,5:m][hc$order]
colnames(data)[5:m] <- colnames(data)[5:m][hc$order]
# Round data
data[,5:m] <- signif(data[,5:m], digits = 4)
levels(data[,1]) <- c(levels(data[,1]),"1","GID","AID","EWEIGHT")
levels(data[,2]) <- c(levels(data[,2]),"1","UNIQID")
levels(data[,3]) <- c(levels(data[,3]),"1","NAME")
data <- rbind(1,data)
nom <- c("GID","UNIQID","NAME","GWEIGHT",names(data)[-c(1,2,3,4)])
names(data) <- nom
data[1,1] <- "EWEIGHT"
data <- rbind(c("AID",NA,NA,NA,paste('ARRY',hc$order-1,'X',sep='')),data)
# NA will be replaced by "" in the file
# data[2:length(data[,1]),2] <- NA
data[2,2:4] <- NA
# Write file
if(dec==',')
{
data<-apply(data,2,function(u){chartr(".",",",u)})
data[data=="NA"]<-NA
}
write.table(data,file = file,sep = '\t',row.names = FALSE,col.names = TRUE,na="",quote=FALSE)
}
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