Learn mapping with Cancer Cell | Correlation heat map (asymmetric version)

cor_heapmap

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R, Fong C, Smith S, Riely GJ, Rudin CM, Gomez DR, Solit DB, Berger MF, Li BT, Mayo MW, Matei I, Lyden DC, Adusumilli PS, Schultz N, Sanchez-Vega F, Jones DR. Genomic mapping of metastatic organotropism in lung adenocarcinoma. Cancer Cell. 2023 May 8;41(5):970-985.e3. doi: 10.1016/j.ccell.2023.03.018.
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In fact, the diagram is Co-occurrence and mutual exclusivity of genes. According to the mode of action of synergy and mutual exclusion, mutations can be divided into the following two categories: "1. Co-occurencing mutations; 2. Mutually exclusive mutations" . Mutually exclusive driver genes often share genes in the same pathway (Pathway) or different progression pathways (such as different tumor types).

For convenience here, we directly use the results of correlation analysis to draw the graph.

The difficulty of this figure is that the upper and lower triangles only display the positive and negative correlation values j and their corresponding significance marks respectively. We only need to perform preliminary preprocessing on the data.

Reproducible results

fig

Sample data and code collection

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Drawing

rm(list = ls())
library(corrplot)
# 准备数据（示例数据）
cor_matrix <- cor(mtcars)  # 使用mtcars数据集作为示例数据

# 创建相关性矩阵
corr_matrix <- cor_matrix  # 复制相关性矩阵

corr_matrix[corr_matrix == 1] <- NA # 将值为1的元素替换为NA
corr_matrix[upper.tri(corr_matrix) & corr_matrix > 0] <- 0  # 上三角大于0的值替换为0
corr_matrix[lower.tri(corr_matrix) & corr_matrix < 0] <- 0  # 下三角小于0的值替换为0


p.mat <- cor.mtest(cor_matrix)$p  # 计算相关系数的显著性
# 预处理使得显著性只显示在对应的区域
# 这一步为了让结果好看 有点问题 大家可以加群讨论
p.mat[p.mat == 0] <- 0 
p.mat[corr_matrix != 0] <- 1
# 创建热图
library(ComplexHeatmap)

ht_list <- Heatmap(
  corr_matrix, 
  name = " ", 
  border = "white",
  col = colorRampPalette(c("#417e46", "#f7f8f9", "#6f2f7e"))(100),
  rect_gp = gpar(col = "white", lwd = 2),
  column_order = colnames(corr_matrix),
  row_order = rownames(corr_matrix),
  row_names_side = "left",  # 行标签放在左边
  column_names_side = "top",   # 列标签放在上边
  row_names_gp = gpar(
    fontsize = 10),
  column_names_gp = gpar(
    fontsize = 10),
  heatmap_legend_param = list(
  title = "correlation", 
  direction = "horizontal",
  legend_width = unit(10, "cm"),
  legend_height = unit(4, "cm")),
  cell_fun = function(j, i, x, y, w, h, fill) {
    if(p.mat[i, j] > 0.05) { # 为了结果美观修改，实际上因该上<0.05,可以加群讨论
      grid.text("*", x, y,
                gp = gpar(col = 'white',
                          fontsize = 25))
    } 
  }
  )
pdf('cor_heapmap.pdf',width = 8,height = 8)
draw(ht_list, heatmap_legend_side = "bottom")
dev.off()

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