R语言 聚类分析 r语言聚类分析树状图

这里做简单的翻译和备份，有关聚类的R包可以参考cluster包和ape包

以下是正文：

The most basic dendrogram

mtcars dataset and we'll calculate a hierarchical clustering with the functionhclust

让我们从最基本聚类树状图开始。为此目的，我们将使用mtcars数据集和我们计算的层次聚类hclust函数（与默认选项）。

# prepare hierarchical cluster 生成层次聚类 

hc = hclust(dist(mtcars))

# very simple dendrogram     默认画法

plot(hc)

We can put the labels of the leafs at the same level like this 

我们可以将样本定义在同一水平 （实在不明白help一下plot函数）

A less basic dendrogram

In order to add more format to the dendrograms, we need to tweek the right parameters. For instance, we could get the following graphic (just for illustration purposes!)

一个更基本的树状图

为了增加更多格式的图，我们需要修改正确的参数。例如，我们可以得到下面的图形（仅作说明用途！）

par(op)

##这里强调一下，par（）是对图进行自动调整，貌似功能还挺强大的。新浪有位哥们儿总结得特别好，附赠地址：

http://blog.sina.com.cn/s/blog_8f5b2a2e0102v0tf.html

貌似可以靠par（）函数调整图的坐标轴什么的，我没试过哦~~

Alternative dendrograms

An alternative way to produce dendrograms is to specifically convert  hclust  objects into dendrograms  objects

另类聚类图

将hclude生成的对象转换为另类的聚类图

# using dendrogram objects
hcd = as.dendrogram(hc)
# alternative way to get a dendrogram
plot(hcd)

dendrogram, we can also plot the branches in a triangular form

画完这个画三角形的

Zooming-in on dendrograms

Another very useful option is the ability to inspect selected parts of a given tree. For instance, if we wanted to examine the top partitions of the dendrogram, we could cut it at a height of 75

放大在树状图

另一个非常有用的功能是选择树的一部分。例如，如果我们要研究的树状图上的分区，我们可以把它在一个高度75

# plot dendrogram with some cuts

op = par(mfrow = c(2, 1))

plot(cut(hcd, h = 75)$upper, main = "Upper tree of cut at h=75")

plot(cut(hcd, h = 75)$lower[[2]], main = "Second branch of lower tree with cut at h=75")

par(op)

Customized dendrograms

dendrapply

为了获得更多的定制的图形，我们需要更多的代码。一个非常有用的功能dendrapply可以应用一个函数的一dendrgoram所有节点。如果我们要添加一些色彩的标签这是非常方便的。

# vector of colors labelColors = c('red', 'blue', 'darkgreen', 'darkgrey',
# 'purple')
labelColors = c("#CDB380", "#036564", "#EB6841", "#EDC951")
# cut dendrogram in 4 clusters
clusMember = cutree(hc, 4)
# function to get color labels
colLab <- function(n) {
    if (is.leaf(n)) {
        a <- attributes(n)
        labCol <- labelColors[clusMember[which(names(clusMember) == a$label)]]
        attr(n, "nodePar") <- c(a$nodePar, lab.col = labCol)
    }
    n
}
# using dendrapply
clusDendro = dendrapply(hcd, colLab)
# make plot
plot(clusDendro, main = "Cool Dendrogram", type = "triangle")

Phylogenetic trees

ape. In this case, what we need is to convert thehclust objects intophylo pbjects with the funtions as.phylo

系统进化树

由R包ape提供更具吸引力的树非常好的工具，我们利用as.phylo功能将hclust objects转换成phylo对象

# load package ape; remember to install it: install.packages('ape')

library(ape)

# plot basic tree

plot(as.phylo(hc), cex = 0.9, label.offset = 1)

plot.phylo

plot.phylo函数的4种不同类型的聚类树形图

# cladogram
plot(as.phylo(hc), type = "cladogram", cex = 0.9, label.offset = 1)

# unrooted
plot(as.phylo(hc), type = "unrooted")

下面是我最喜欢的圆形树形图

# fan    
plot(as.phylo(hc), type = "fan")

# radial
plot(as.phylo(hc), type = "radial")

Customizing phylogenetic trees

ape

自定义的系统进化树

ape 包对树的性状有着很多控制，能够定制他们以不同的方式。例如：

# add colors randomly
plot(as.phylo(hc), type = "fan", tip.color = hsv(runif(15, 0.65, 
    0.95), 1, 1, 0.7), edge.color = hsv(runif(10, 0.65, 0.75), 1, 1, 0.7), edge.width = runif(20, 
    0.5, 3), use.edge.length = TRUE, col = "gray80")

Again, we can tweek some parameters according to our needs

我们可以根据需求修改一些参数

# vector of colors
mypal = c("#556270", "#4ECDC4", "#1B676B", "#FF6B6B", "#C44D58")
# cutting dendrogram in 5 clusters
clus5 = cutree(hc, 5)
# plot
op = par(bg = "#E8DDCB")
# Size reflects miles per gallon
plot(as.phylo(hc), type = "fan", tip.color = mypal[clus5], label.offset = 1, 
    cex = log(mtcars$mpg, 10), col = "red")

par(op)

---

Color in leaves

彩色叶子节点

sparcl provides the ColorDendrogram

ColorDendrogram功能来让我们给聚类树点颜色看看。比如我们可以给叶子节点来点颜色

# install.packages('sparcl')
library(sparcl)
# colors the leaves of a dendrogram
y = cutree(hc, 3)
ColorDendrogram(hc, y = y, labels = names(y), main = "My Simulated Data", 
    branchlength = 80)

ggdendro

ggplot2 have no functions to plot dendrograms. However, the ad-hoc packageggdendro

R包ggplot2没有功能绘制树状图的原因我不知道。然而，包ggdendro提供一个像样的解决方案。你希望有更多的自定义选项，但到目前为止他们相当有限。不管怎样，对于我们这些谁是ggploters这是我们工具的另一个工具。

# install.packages('ggdendro')
library(ggdendro)
# basic option
ggdendrogram(hc)

# another option
ggdendrogram(hc, rotate = TRUE, size = 4, theme_dendro = FALSE, color = "tomato")

# Triangular lines
ddata <- dendro_data(as.dendrogram(hc), type = "triangle")
ggplot(segment(ddata)) + geom_segment(aes(x = x, y = y, xend = xend, 
    yend = yend)) + ylim(-10, 150) + geom_text(data = label(ddata), aes(x = x, 
    y = y, label = label), angle = 90, lineheight = 0)

---

Colored dendrogram

addicted to Rgraph gallery which I find really interesting. The code in R for generating colored dendrograms, which you can download and modify if wanted so, is availablehere

最后，你可以到罗曼弗朗索瓦的图形库里面进一步学习~~~

你甚至可以修改他的代码

地址是：

http://gallery.r-enthusiasts.com/RGraphGallery.php?graph=79 （貌似要FQ）

http://addictedtor.free.fr/packages/A2R/lastVersion/R/code.R

# load code of A2R function
source("http://addictedtor.free.fr/packages/A2R/lastVersion/R/code.R")
# colored dendrogram
op = par(bg = "#EFEFEF")
A2Rplot(hc, k = 3, boxes = FALSE, col.up = "gray50", col.down = c("#FF6B6B", 
    "#4ECDC4", "#556270"))

par(op)

# another colored dendrogram
op = par(bg = "gray15")
cols = hsv(c(0.2, 0.57, 0.95), 1, 1, 0.8)
A2Rplot(hc, k = 3, boxes = FALSE, col.up = "gray50", col.down = cols)

par(op)

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