R:如何显示聚类矩阵热图(类似的颜色模式分组) [英] R: How do I display clustered matrix heatmap (similar color patterns are grouped)

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问题描述

我在整个网站和软件包中搜索了很多关于热图的问题,但我仍然有一个问题。


我有集群数据(kmeans / EM / DBscan ..),我想通过对同一个集群进行分组来创建一个热图。我希望类似的颜色模式能够在热图中分组,所以一般来说,它看起来像块对角线。

我尝试按簇号对数据进行排序并显示它,

  k = kmeans(data,3)
d = data.frame(data)
d = data.frame(d,k $ cluster)
d = d [order(d $ k.cluster),]
heatmap(as.matrix (d))

但它仍然没有排序,看起来像这样的链接:

我可以在R中做这个吗?

我搜索了很多软件包并尝试了很多方法,但我仍然有一个问题。

非常感谢。

解决方案

您可以使用 reshape2 和 ggplot2 如下:

 图书馆(reshape2)
library(ggplot2)

#创建虚拟数据
set.seed(123)
df< - data.frame(
a =样品(1:5,1000,repl ace = TRUE),
b = sample(1:5,1000,replace = TRUE),
c = sample(1:5,1000,replace = TRUE)


#执行聚类
k < - kmeans(df,3)

#附加id和集群
dfc< - cbind(df,id = seq(nrow df)),cluster = k $ cluster)

#添加idsort,按集群顺序排列的id号
dfc $ idsort< - dfc $ id [order(dfc $ cluster)]
dfc $ idsort< - order(dfc $ idsort)

#使用reshape2 :: melt以长格式创建data.frame
dfm< - melt(dfc,id .vars = c(id,idsort))

ggplot(dfm,aes(x = variable,y = idsort))+ geom_tile(aes(fill = value))


I searched a lot of questions about heatmap throughout the site and packages, but I still have a problem.
I have clustered data (kmeans/EM/DBscan..), and I want to create a heatmap by grouping the same cluster. I want the similar color patterns to be grouped in the heatmap, so generally, it looks like a block-diagonal.
I tried to order the data by the cluster number and display it,

k = kmeans(data, 3)
d = data.frame(data)
d = data.frame(d, k$cluster)
d = d[order(d$k.cluster),]
heatmap(as.matrix(d))

but it is still not sorted and looks like this link:
But, I want it to be sorted by its cluster number and looked like this:
Can I do this in R?
I searched lots of packages and tried many ways, but I still have a problem.
Thanks a lot.

解决方案

You can do this using reshape2 and ggplot2 as follows:

library(reshape2)
library(ggplot2)

# Create dummy data
set.seed(123)
df <- data.frame(
        a = sample(1:5, 1000, replace=TRUE),
        b = sample(1:5, 1000, replace=TRUE),
        c = sample(1:5, 1000, replace=TRUE)
)

# Perform clustering
k <- kmeans(df, 3)

# Append id and cluster
dfc <- cbind(df, id=seq(nrow(df)), cluster=k$cluster)

# Add idsort, the id number ordered by cluster 
dfc$idsort <- dfc$id[order(dfc$cluster)]
dfc$idsort <- order(dfc$idsort)

# use reshape2::melt to create data.frame in long format
dfm <- melt(dfc, id.vars=c("id", "idsort"))

ggplot(dfm, aes(x=variable, y=idsort)) + geom_tile(aes(fill=value))

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