我想将R中的hclust-dendrogram导出到数据表中,以便随后将其导入另一个(“自制”)软件。 str(unclass(fit))
提供了树形图的文本概述,但我正在寻找的是一个数字表。我看过Bioconductor ctc软件包,但它产生的输出看起来有点密码。我希望得到类似于此表的内容:http://stn.spotfire.com/spotfire_client_help/heat/heat_importing_exporting_dendrograms.htm
有没有办法从R中的hclust对象中得到这个?
答案 0 :(得分:3)
如果有人对树形图出口感兴趣,这是我的解决方案。最有可能的是,它不是最好的,因为我最近才开始使用R,但至少它起作用了。因此欢迎有关如何改进代码的建议。
因此,如果hr
是我的hclust对象而df
是我的数据,则其第一列包含从0开始的简单索引,行名称是群集项的名称:
# Retrieve the leaf order (row name and its position within the leaves)
leaf.order <- matrix(data=NA, ncol=2, nrow=nrow(df),
dimnames=list(c(), c("row.num", "row.name")))
leaf.order[,2] <- hr$labels[hr$order]
for (i in 1:nrow(leaf.order)) {
leaf.order[which(leaf.order[,2] %in% rownames(df[i,])),1] <- df[i,1]
}
leaf.order <- as.data.frame(leaf.order)
hr.merge <- hr$merge
n <- max(df[,1])
# Re-index all clustered leaves and nodes. First, all leaves are indexed starting from 0.
# Next, all nodes are indexed starting from max. index leave + 1.
for (i in 1:length(hr.merge)) {
if (hr.merge[i]<0) {hr.merge[i] <- abs(hr.merge[i])-1}
else { hr.merge[i] <- (hr.merge[i]+n) }
}
node.id <- c(0:length(hr.merge))
# Generate dendrogram matrix with node index in the first column.
dend <- matrix(data=NA, nrow=length(node.id), ncol=6,
dimnames=list(c(0:(length(node.id)-1)),
c("node.id", "parent.id", "pruning.level",
"height", "leaf.order", "row.name")) )
dend[,1] <- c(0:((2*nrow(df))-2)) # Insert a leaf/node index
# Calculate parent ID for each leaf/node:
# 1) For each leaf/node index, find the corresponding row number within the merge-table.
# 2) Add the maximum leaf index to the row number as indexing the nodes starts after indexing all the leaves.
for (i in 1:(nrow(dend)-1)) {
dend[i,2] <- row(hr.merge)[which(hr.merge %in% dend[i,1])]+n
}
# Generate table with indexing of all leaves (1st column) and inserting the corresponding row names into the 3rd column.
hr.order <- matrix(data=NA,
nrow=length(hr$labels), ncol=3,
dimnames=list(c(), c("order.number", "leaf.id", "row.name")))
hr.order[,1] <- c(0:(nrow(hr.order)-1))
hr.order[,3] <- t(hr$labels[hr$order])
hr.order <- data.frame(hr.order)
hr.order[,1] <- as.numeric(hr.order[,1])
# Assign the row name to each leaf.
dend <- as.data.frame(dend)
for (i in 1:nrow(df)) {
dend[which(dend[,1] %in% df[i,1]),6] <- rownames(df[i,])
}
# Assign the position on the dendrogram (from left to right) to each leaf.
for (i in 1:nrow(hr.order)) {
dend[which(dend[,6] %in% hr.order[i,3]),5] <- hr.order[i,1]-1
}
# Insert height for each node.
dend[c((n+2):nrow(dend)),4] <- hr$height
# All leaves get the highest possible pruning level
dend[which(dend[,1] <= n),3] <- nrow(hr.merge)
# The nodes get a decreasing index starting from the pruning level of the
# leaves minus 1 and up to 0
for (i in (n+2):nrow(dend)) {
if ((dend[i,4] != dend[(i-1),4]) || is.na(dend[(i-1),4])){
dend[i,3] <- dend[(i-1),3]-1}
else { dend[i,3] <- dend[(i-1),3] }
}
dend[,3] <- dend[,3]-min(dend[,3])
dend <- dend[order(-node.id),]
# Write results table.
write.table(dend, file="path", sep=";", row.names=F)
答案 1 :(得分:1)
有一个包与你想要的完全相反 - Labeltodendro; - )
但严重的是,您不能手动从hclust
对象(例如$merge
,$height
,$order
)中提取元素,并从提取的元素中创建自定义表格?