可视化系列【二】：跟着Nature Communications

不积跬步，无以至千里

本期我们同样尝试复现2023年2月27日发表在Nature Communications上的Itaconate ameliorates autoimmunity by modulating T cell imbalance via metabolic and epigenetic reprogramming文章中的Fig2A。

以下是原图：

数据可以自行下载，也可评论区留言我私发给你。

代码

library(tidyverse)
library(readr)
library(dplyr)
library(magrittr)
library(ggplot2)

data <- read_csv(file = 'fig3f.csv') %>% 
  pivot_longer(cols = c('Ctrl', 'ITA'), names_to = 'Category') %>% 
  na.omit()

SEM <- function(vec) sd(vec, na.rm = T)/sqrt(length(!is.na(vec)))
summary_min <- function(x) mean(x) - SEM(x)
summary_max <- function(x) mean(x) + SEM(x)

ggplot(data = data, aes(x = Category, y = value)) + 
  stat_summary(aes(color = Category),
               geom = 'errorbar',
               width = 0.3,
               size = 1,
               fun.min = summary_min,
               fun.max = summary_max) +
  geom_bar(aes(color = Category), 
           stat = "summary", 
           fun = "mean", 
           fill = 'white', 
           size = 1, 
           width = 0.5) +
  scale_y_continuous(expand = c(0, 0), limits = c(0, 5)) +
  geom_jitter(aes(color = Category), size = 1.5, width = 0.25, fill = NA, shape = 1, stroke = 1.5) + 
  annotate(geom = 'segment', x = 1, xend = 2, y = 4.3, yend = 4.3, size = 1) +
  annotate(geom = 'text', 
           label = "paste(italic(P), \" = 0.0185\")", 
           x = 1.5, 
           y = 4.3, 
           vjust = -1, 
           family = 'sans',
           parse = TRUE) +
  labs(x = '', y = 'Inflammation score') +
  scale_color_manual(values = c('#1437B1', '#F0368E')) +
  theme_classic() +
  theme(legend.position = 'none',
        axis.title = element_text(family = 'sans', color = 'black', size = 15),
        axis.text = element_text(family = 'sans', color = 'black', size = 15),
        axis.line = element_line(color = 'black', size = 0.9),
        axis.ticks = element_line(color = 'black', size = 0.9),
        axis.ticks.length = unit(.07, units = 'in')) 
ggsave(filename = 'Fig3f.jpeg', dpi = 5000, width = 2, height = 3)

最终效果

写在最后

这个图里面有几个我觉得是值得我们大家一起学习的：

• stat_summary()函数添加errorbar；

• 使用stroke参数控制空心点的边界粗细；

• 使用label = "paste(italic(P), \" = 0.0185\")"将P显示为P。