如何通过R中的附加因子变量为树形图的标签着色 [英] How to colour the labels of a dendrogram by an additional factor variable in R
问题描述
我使用下面的代码在R中运行层次聚类分析后生成了一个树形图。我现在试图根据另一个因子变量,将其保存为向量的颜色标签。我最近实现这一点是使用 sparcl
包中的 ColourDendrogram
函数对分支进行颜色编码。如果可能,我更喜欢对标签进行颜色编码。我在以下链接中找到了类似问题的答案:树状图的颜色分支使用现有列& 在R 的树状图中着色分支,但我还没能以解决如何转换示例代码为我的目的。下面是一些示例数据和代码。
I have produced a dendrogram after running hierarchical clustering analysis in R using the below code. I am now trying to colour the labels according to another factor variable, which is saved as a vector. The closest that I have come to achieving this is to colour code the branches using the ColourDendrogram
function in the sparcl
package. If possible, I would prefer to colour-code the labels. I have found answers to a similar questions at the following links Color branches of dendrogram using an existing column & Colouring branches in a dendrogram in R, but I have not been able to work out how to convert the example code for my purpose. Below is some example data and code.
> dput(df)
structure(list(labs = c("a1", "a2", "a3", "a4", "a5", "a6", "a7",
"a8", "b1", "b2", "b3", "b4", "b5", "b6", "b7"), var = c(1L,
1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L), td = c(13.1,
14.5, 16.7, 12.9, 14.9, 15.6, 13.4, 15.3, 12.8, 14.5, 14.7, 13.1,
14.9, 15.6, 14.6), fd = c(2L, 3L, 3L, 1L, 2L, 3L, 2L, 3L, 2L,
4L, 2L, 1L, 4L, 3L, 3L)), .Names = c("labs", "var", "td", "fd"
), class = "data.frame", row.names = c(NA, -15L))
df.nw = df[,3:4]
labs = df$labs
d = dist(as.matrix(df.nw)) # find distance matrix
hc = hclust(d, method="complete") # apply hierarchical clustering
plot(hc, hang=-0.01, cex=0.6, labels=labs, xlab="") # plot the dendrogram
hcd = as.dendrogram(hc) # convert hclust to dendrogram
plot(hcd, cex=0.6) # plot using dendrogram object
Var = df$var # factor variable for colours
varCol = gsub("1","red",Var) # convert numbers to colours
varCol = gsub("2","blue",varCol)
# colour-code dendrogram branches by a factor
library(sparcl)
ColorDendrogram(hc, y=varCol, branchlength=0.9, labels=labs,
xlab="", ylab="", sub="")
任何建议如何做非常感谢。
Any advise on how to do this would be greatly appreciated.
推荐答案
尝试
# ... your code
colLab <- function(n) {
if(is.leaf(n)) {
a <- attributes(n)
attr(n, "label") <- labs[a$label]
attr(n, "nodePar") <- c(a$nodePar, lab.col = varCol[a$label])
}
n
}
plot(dendrapply(hcd, colLab))
b $ b
(通过)
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