此post旨在提取heatmap作图中的cluster行名或者列名

其实，对heatmap热图提取cluster就是对hclust的结果提取cluster，tree_col和tree_row属性

首先，我们要构建一个matrix或者data.frame进行pheatmap作图

# package library
library(pheatmap)
library(tidyverse)

# Create random data
set.seed(50)
data <- replicate(20, rnorm(50, mean = 100, sd = 100))
data %>% class()

rownames(data) <- paste("Gene", c(1:nrow(data)))
colnames(data) <- paste("Sample", c(1:ncol(data)))

# get heatmap plot
(out <- pheatmap(data, scale="row"))
dev.copy(png, "heatmap_raw.png", width=4000, height=4000, res = 330)
dev.off()

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随后，我们提取热图中的行名和列名

# Re-order original data (genes) to match ordering in heatmap (top-to-bottom)
data[out$tree_row[["order"]],] %>% rownames()

# Re-order original data (samples) to match ordering in heatmap (left-to-right)
data[out$tree_row[["order"]],] %>% colnames()

# get hclust plot
plot(out$tree_col)
abline(h = 11.5, col="red", lty=2, lwd=2)
dev.copy(png, "heatmap_hclust.png", width=4000, height=4000, res = 330)
dev.off()

[图片上传失败...(image-3b19fa-1651998649328)]

假如我们需要可视化的话，可以加一个annotation

# get 3 cluster for sample name
(tree <- cutree(out$tree_col, k=3))

tree <- ifelse(tree == 1, "cluster_1", 
               ifelse(tree == 2, "cluster_2", 
                      "cluster_3")) %>% as.data.frame() %>% setNames("Cluster")

# get annotation plot
pheatmap(data, scale = "row", annotation_col = tree)
dev.copy(png, "heatmap_3cluster.png", width=4000, height=4000, res = 330)
dev.off()

[图片上传失败...(image-837391-1651998607583)]