ggpolt2构建差异基因热图

R语言数据分析指南

发布于 2023-10-17 14:51:36

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❝本节分享如何基于差异基因分析的结果来绘制热图，主要还是基于ggplot2体系来实现，针对以往的代码风格，这次小编通过拆分数据定义每一部分的函数来编写新的代码，希望对各位观众老爷能有新的帮助，数据和代码已经被打包并上传到小编的2023VIP会员交流群。已经加群的朋友可以自行下载。如果你需要，可以参考文末的方式进行购买。 ❞

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加载R包

library(tidyverse)
library(ggtree)
library(aplot)
library(scico)

读取并处理数据

process_data <- function() {
  gene <- read_tsv("diff.txt") %>% 
    arrange(desc(abs(logFC))) %>% 
    head(11) %>% 
    pull(id)
  
  df <- read_tsv("diffGeneExp.txt") %>% 
    pivot_longer(-id) %>% 
    filter(id %in% gene) %>% 
    pivot_wider(., names_from=name, values_from=value) %>% 
    column_to_rownames(var="id")
  
  dff <- df %>% 
    scale() %>% 
    as.data.frame() %>% 
    rownames_to_column(var="id") %>% 
    pivot_longer(-id) %>% 
    mutate(type = map_chr(name, ~str_split(.x, "_")[[1]][length(str_split(.x, "_")[[1]])]))
  
  list(df = df, dff = dff)
}

生成热图

generate_heatmap <- function(dff) {
  ggplot(dff, aes(name, id, fill=value)) +
    geom_tile() +
    scale_y_discrete(position = "right", expand = c(0,0)) +
    scale_fill_scico(palette = 'cork') +
    labs(x=NULL, y=NULL) +
    theme(axis.text.x=element_blank(),
          axis.text.y=element_text(color="black", size=8),
          axis.ticks = element_blank(),
          panel.background = element_blank(),
          plot.background = element_blank(),
          legend.background = element_blank(),
          legend.title =element_blank())
}

生成树状图

generate_tree <- function(df) {
  hclust(dist(df, method = "binary")) %>% 
    ggtree(layout="rectangular", branch.length="none") +
    theme_void()
}

生成类型图

generate_type_plot <- function(dff) {
  dff %>% 
    mutate(Type='Type') %>% 
    ggplot(aes(name, Type, fill=type)) +
    geom_tile() +
    scale_y_discrete(position = "right", expand = c(0,0)) +
    scale_fill_manual(values=c("#3B9AB2","#78B7C5")) +
    theme(panel.background = element_blank(),
          axis.ticks = element_blank(),
          axis.title = element_blank(),
          axis.text.x = element_blank(),
          plot.background = element_blank())
}

主函数

main <- function() {
  data <- process_data()
  heatmap <- generate_heatmap(data$dff)
  phr <- generate_tree(data$df)
  type_plot <- generate_type_plot(data$dff)
  
  heatmap %>% 
    insert_left(phr, width = 0.2) %>% 
    insert_top(type_plot, height = 0.08)
}