加载需要的R包：
library(reshape2)
library(ggplot2)
library(ggtree) #需要在bioconductor下载
读入数据：
gene <- read.csv(file = "clipboard",header = T,sep = "\t",check.names = F,row.names = 1)
gene
gg <- hclust(dist(gene)) #对行聚类
zz <- hclust(dist(t(gene))) #对列聚类
gene <- gene[,zz$order] #列，按照聚类结果排序
gene <- gene[gg$order,] #行，按照聚类结果排序
gene <- cbind(name = row.names(gene),gene)
data <- melt(gene,id.vars = "name") #宽数据变为长数据
data$num <- rep(c(1:26),6) #绘图时的纵坐标
data$x <- rep(c(1:6),each = 26) #绘图时的横坐标
开始绘图：
heatmap <- ggplot(data)+
geom_tile(aes(x = x,y = num,alpha = 0.7),fill = "white",color = "gray")+
geom_point(aes(x = x,y = num,size = value,color = value),shape = 18)+
scale_color_gradient2(low = "green",high = "red",mid = "white",midpoint = 6,name = "FPKM",
guide = guide_colourbar(barheight = unit(10,"cm"),title.theme = element_text(size = rel(15))))+
scale_y_discrete(position = c("right"),limits = factor(c(1:26)),label = gene$name)+
scale_x_discrete(limits = factor(c(1:6)),label = c(colnames(gene)[2:7]))+
scale_size_continuous(range = c(4,9),guide = NULL)+
scale_alpha(guide = NULL)+
labs(x = NULL)+
theme(panel.background = element_blank(),
axis.line.x = element_blank(),
axis.line.y = element_blank(),
axis.title.y = element_blank(),
axis.title.x = element_text(size = rel(2),hjust = 0.5),
axis.text.x = element_text(size = rel(2),hjust = 0.5),
axis.text.y = element_text(hjust = 0.5,size = rel(2)),
axis.ticks.x = element_blank(),
axis.ticks.y = element_blank(),
plot.title = element_text(size = rel(1.8)),
plot.margin = margin(15,9,9,30))
绘制聚类树：
h <- ggtree(gg,layout = "rectangular",branch.length = "none") # 绘制列聚类树
v <- ggtree(zz)+layout_dendrogram() # 绘制行聚类树
绘制分组信息：
group <- rep(c("A","B"),each = 3) %>% data.frame(x = c(1:6),y = rep(1,6)) %>%
ggplot()+
geom_tile(aes(x,y,fill = .))+
scale_fill_discrete(label = c("control","treat"))+
theme(panel.background = element_blank(),
axis.line = element_blank(),
axis.title = element_blank(),
axis.text = element_blank(),
axis.ticks = element_blank(),
plot.title = element_blank())
热图和聚类树拼在一起：
heatmap %>% insert_top(group,height = 0.02) %>% insert_top(v,height = 0.1) %>% insert_left(h,width = 0.3) #使用 aplot包里的函数进行拼图
最终结果：
