我之前写过一篇用R中pheatmap画heatmap
这篇实践一种交互式的方法 iheatmapr
参考这里：
iheatmapr包：可交互的热图绘制方法——生信宝典
iheatmapr的帮助文档

1. 安装iheatmapr包

install.packages("iheatmapr")
#如果R 版本不对可能会需要下面这行
BiocManager::install("S4Vectors")

2. library所需包

library(iheatmapr)
library(datasets)
library(reshape2)

3. 使用acast调用datasets包内的Indometh数据集的内容

Indometh_matrix <- acast(Indometh, Subject ~ time, value.var = "conc")
Indometh_matrix <- Indometh_matrix[as.character(1:6),]
rownames(Indometh_matrix) <- paste("Patient",rownames(Indometh_matrix))

4. 计算相关性矩阵

Indometh_patient_cor <- cor(t(Indometh_matrix))

5. 取每个样本数据中的最大值和最小值

patient_max_conc <- apply(Indometh_matrix,1,max)
patient_min_conc <- apply(Indometh_matrix,1,min)

6. 给每个样本随机分配一个分组

patient_groups <- c("A","A","B","A","B","B")

7. 绘制相关性矩阵热图

example_heatmap <- main_heatmap(Indometh_patient_cor, name = "Correlation")
example_heatmap

雏形

8. 一些修饰

8.1 colors修改颜色

main_heatmap(Indometh_patient_cor,
             colors = "Pinks",
             name = "Correlation")

colors修改颜色

8.2 两幅热图同时呈现

main_heatmap(Indometh_patient_cor, name = "Correlation") %>%
  add_main_heatmap(Indometh_matrix, name = "Indometacin<br>Concentration")

两幅热图

8.3 添加标签

main_heatmap(Indometh_matrix, name="Correlation") %>%
  add_row_labels() %>%
  add_col_labels() %>%
  add_row_title("Patients", buffer=0.2) %>%
  add_col_title("Patients", buffer=0.1)

buffer表示：title文字与图之间的距离

添加标签

8.4 添加聚类

main_heatmap(Indometh_patient_cor) %>%
   add_row_clustering() %>%
   add_col_clustering()

聚类后的数据

8.5 添加样本注释

main_heatmap(Indometh_patient_cor) %>%
 add_row_annotation(data.frame("Max" = patient_max_conc,
                            "Min" = patient_min_conc,
                            "Groups" = c("A","A","B","B","A","B")),
                             colors = list("Max" = "Reds",
                            "Min" = "Blues",
                            "Groups" = c("purple","pink")))

样本注释

除了add_row_annotation，还可以使用add_row_signal和add_row_groups添加注释。

main_heatmap(Indometh_patient_cor) %>%
  add_row_signal(patient_max_conc, "Max<br>Concentration", title = "Max", colors = "Reds") %>%
  add_row_signal(patient_min_conc, "Min<br>Concentration", title = "Min", colors = "Reds") %>%
  add_row_groups(c("A","A","B","B","A","B"), "Groups")

---

这里一份完整的参数，随用随改

main_heatmap(Indometh_patient_cor,name = "Correlation") %>%
  add_col_clustering() %>%
  add_row_clustering(k = 3) %>%
  add_row_title("Patients") %>%
  add_col_title("Patients") %>%
  add_row_annotation(data.frame("Max" = patient_max_conc,
                                "Min" = patient_min_conc,
                                "Groups" = patient_groups)) %>%
  add_main_heatmap(Indometh_matrix,
                   name = "Indometacin<br>Concentration") %>%
  add_col_labels() %>%
  add_col_title("Time") %>%
  add_col_summary()