跟着Nature Genetics学做图：R语言ggplot2做热图展示基因存在缺失变异

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发布于 2023-12-19 15:19:32

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发布于 2023-12-19 15:19:32

文章被收录于专栏：小明的数据分析笔记本小明的数据分析笔记本

论文

Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice

今天的推文来试着复现一下论文中的figure5a

自己构造的示例数据部分截图

image.png

读取数据

library(readxl)
library(tidyverse)
dat<-read_excel("data/20231219/20131219.xlsx") %>% 
  mutate(group3=case_when(
    group2 == 0 ~ "0",
    TRUE ~ group1
  ))
dat %>% head()

dat %>% pull(x) %>% unique() -> x.levels
dat %>% pull(y) %>% unique() -> y.levels

组图代码

library(ggplot2)
dat %>% 
  mutate(x=factor(x,levels = x.levels),
         y=factor(y,levels = rev(y.levels))) %>% 
  ggplot(aes(x=x,y=y))+
  geom_tile(aes(fill=group3),
            color="gray")+
  theme_bw(base_size = 15)+
  theme(panel.grid = element_blank(),
        panel.border = element_blank(),
        axis.ticks = element_blank(),
        axis.title = element_blank(),
        axis.text.x = element_text(angle=90,hjust=0),
        axis.text.y = element_text(face = "italic"))+
  scale_x_discrete(position = "top",
                   expand = c(0,0))+
  scale_y_discrete(expand = c(0,0))+
  scale_fill_manual(values = c("0"="white",
                               "A"="#fe0000",
                               "B"="#c0a100",
                               "D"="#00b650",
                               "E"="#f38dd5",
                               "F"="#7230a3",
                               "G"="#02b5fc"))+
  theme(legend.position = "none")