跟着Nature学作图：R语言ggplot2频率分布直方图

用户7010445

发布于 2023-01-06 19:09:10

1.6K0

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

Graph pangenome captures missing heritability and empowers tomato breeding

https://www.nature.com/articles/s41586-022-04808-9#MOESM8

没有找到论文里的作图的代码，但是找到了部分组图数据，我们可以用论文中提供的原始数据模仿出论文中的图

今天的推文重复一下论文中的Figure2c 频率分布直方图

image.png

部分示例数据截图

image.png

作图数据用到的是R2那一列

读取数据集

library(readxl)

dat.fig2c<-read_excel("data/20220711/41586_2022_4808_MOESM6_ESM.xlsx",
                      sheet = "Fig2c",
                      skip = 1)
head(dat.fig2c)

这里第一行数据没有用，我们可以选择手动删除，或者设置读取数据时不读取第一行

作图代码

library(ggplot2)
library(latex2exp)

ggplot(data=dat.fig2c,aes(x=R2))+
  geom_histogram(aes(y=after_stat(count / sum(count)),
                     fill=Type),
                 bins = 150,
                 alpha=0.3)+
  scale_fill_manual(values = c("InDel-SV"="#a3cd5b",
                               "SNP-SV"="#8ea0cc"),
                    labels=c("InDel-SV"="InDel versus SV",
                             "SNP-SV"="SNP versus SV"))+
  theme_bw()+
  theme(panel.border = element_blank(),
        panel.grid = element_blank(),
        axis.line = element_line(),
        legend.position = c(0.1,0.9),
        legend.direction = "horizontal",
        legend.background = element_rect(fill="transparent"),
        legend.title = element_blank(),
        legend.justification = c(0,1))+
  scale_x_continuous(limits = c(0,1),
                     expand = expansion(mult = c(0,0)))+
  scale_y_continuous(limits = c(0,0.025),
                     expand = expansion(mult = c(0,0)),
                     breaks = seq(0,0.025,0.005),
                     labels = function(x){sprintf("%0.1f",x*100)})+
  labs(x=TeX(r"(\textit{R}$^2$)"),
       y="Frequency (%)")+
  geom_vline(xintercept = 0.7,lty="dashed") -> p1

p1

image.png

这里我个人认为把直方图的边框加上然后颜色深一些可能会好看一点

ggplot(data=dat.fig2c,aes(x=R2))+
  geom_histogram(aes(y=after_stat(count / sum(count)),
                     fill=Type),
                 bins = 150,
                 alpha=1,
                 color="black")+
  scale_fill_manual(values = c("InDel-SV"="#a3cd5b",
                               "SNP-SV"="#8ea0cc"),
                    labels=c("InDel-SV"="InDel versus SV",
                             "SNP-SV"="SNP versus SV"))+
  theme_bw()+
  theme(panel.border = element_blank(),
        panel.grid = element_blank(),
        axis.line = element_line(),
        legend.position = c(0.1,0.9),
        legend.direction = "horizontal",
        legend.background = element_rect(fill="transparent"),
        legend.title = element_blank(),
        legend.justification = c(0,1))+
  scale_x_continuous(limits = c(0,1),
                     expand = expansion(mult = c(0,0)))+
  scale_y_continuous(limits = c(0,0.025),
                     expand = expansion(mult = c(0,0)),
                     breaks = seq(0,0.025,0.005),
                     labels = function(x){sprintf("%0.1f",x*100)})+
  labs(x=TeX(r"(\textit{R}$^2$)"),
       y="Frequency (%)")+
  geom_vline(xintercept = 0.7,lty="dashed") -> p2

p2