可视化—转录组基因表达相关性热图

plot_genes_corr_tianfu <- function(exp_mat, 
                              gene_list, 
                              file_path = "figure/correlation_heatmap.pdf", 
                              width = 7, 
                              height = 7, 
                              triangle = c("lower", "upper"),
                              label_type = c("stars", "pvalue")) {
  
  library(Hmisc)      # rcorr 计算相关系数和 p 值
  library(reshape2)   # melt 矩阵转长格式
  library(ggplot2)
  
  # 参数匹配
  triangle <- match.arg(triangle)
  label_type <- match.arg(label_type)
  
  # 1. 提取指定基因表达矩阵
  gene_mat <- exp_mat[gene_list, ]
  
  # 2. 计算 Pearson 相关系数和 p 值
  res <- rcorr(t(gene_mat), type = "pearson")
  cor_mat <- res$r
  p_mat <- res$P
  
  # 3. 根据参数保留上三角或下三角
  if (triangle == "lower") {
    cor_mat[upper.tri(cor_mat)] <- NA
    p_mat[upper.tri(p_mat)] <- NA
  } else { # upper
    cor_mat[lower.tri(cor_mat)] <- NA
    p_mat[lower.tri(p_mat)] <- NA
  }
  
  # 4. 转换成长格式
  cor_df <- melt(cor_mat, na.rm = TRUE)
  p_df <- melt(p_mat, na.rm = TRUE)
  colnames(cor_df) <- c("Gene1", "Gene2", "Correlation")
  colnames(p_df) <- c("Gene1", "Gene2", "pvalue")
  
  # 5. 合并数据
  plot_df <- merge(cor_df, p_df, by = c("Gene1", "Gene2"))
  
  # 6. 生成标签
  if (label_type == "stars") {
    plot_df$label <- cut(plot_df$pvalue,
                         breaks = c(-Inf, 0.001, 0.01, 0.05, Inf),
                         labels = c("***", "**", "*", ""))
  } else if (label_type == "pvalue") {
    plot_df$label <- formatC(plot_df$pvalue, format = "f", digits = 3)
  }
  
  # 7. 绘制热图
  p <- ggplot(plot_df, aes(x = Gene1, y = Gene2, fill = Correlation)) +
    geom_tile(color = "white") +
    geom_text(aes(label = label), color = "black", size = 4) +
    scale_fill_gradient2(low = "blue", mid = "white", high = "red", midpoint = 0,
                         limits = c(-1, 1), name = "Correlation") +
    theme_minimal() +
    theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 8),
          axis.text.y = element_text(size = 8),
          axis.title = element_blank(),
          panel.grid = element_blank()) +
    coord_fixed()
  
  # 8. 保存 PDF
  ggsave(file_path, p, width = width, height = height)
  
  return(p)
}

#triangle参数控制上三角还是下三角
#label_type参数控制相关性显示*号还是p值
plot_genes_corr_tianfu(exp, related_gene, file_path = "figure/upper_triangle_stars.pdf", 
                  triangle = "upper", 
                  label_type = "stars")