跟着nature学绘图-条图叠加散点与p值

library(tidyverse)
library(scales)
library(ggh4x)
library(ggtext)
library(ggpubr)
library(rstatix)

df <- read_tsv("data.xls") %>% 
  unite(.,col="new_type",group,type,sep="_",remove = F,na.rm = F)

df$new_type <- factor(df$new_type,levels = df$new_type %>% unique())
df$group <- factor(df$group,levels = df$group %>% unique())

df_pval <- df %>% 
  t_test(value ~new_type) %>% 
  adjust_pvalue(p.col="p",method = "bonferroni") %>%
  add_significance(p.col="p.adj",) %>% 
  add_xy_position(x="name") %>% 
  add_xy_position(x="new_type",dodge=0.8) %>% 
  filter(p.adj.signif !="ns") %>% 
  mutate(y.position=c(5.1,7,6.65,6.4)) 


df %>% 
  ggplot(aes(interaction(new_type,group),value))+
  stat_summary(aes(fill=type),alpha=0.5,show.legend = F,
               fun="mean",geom="bar",linewidth=0.4,width = 0.5,color="black")+
  stat_summary(fun.data ="mean_se",geom="errorbar",width=0.2,linewidth=0.3,color="black")+
  stat_pvalue_manual(df_pval,label = "p.adj.signif",hide.ns=F,
                     tip.length=0, label.size=4, color="black")+
  guides(x = "axis_nested")+
  theme_classic()+
  theme(
    axis.ticks.x=element_blank(),
    axis.title.y=element_markdown(color="black",face="bold"),
    axis.text.x=element_blank(),
    axis.text.y=element_text(color="black",size=10,face="bold"),
    plot.margin = margin(0.8,0.5,0.5,0.5,unit="cm"),
    legend.position = "bottom",
    legend.text = element_text(color="black",face="bold")
  )