跟着Nature Metabolism学作图:R语言ggplot2各种各样柱形图(2)

论文

Single-cell profiling of vascular endothelial cells reveals progressive organ-specific vulnerabilities during obesity

https://www.nature.com/articles/s42255-022-00674-x#Sec58

s42255-022-00674-x.pdf

https://github.com/Osynchronika/sc_EC_obesity_atlas

大部分 作图的数据都有，可以试着用论文中提供的数据复现一下论文中的图

论文中figure2和figure3中有很多种柱形图，争取把每个种类的柱形图都复现一下，之前的推文已经出过一期关于柱形图的推文，今天的推文继续柱形图相关

figure4c2 普通柱形图添加误差线和显著性标记

论文中提供的数据如下

需要我们手动整理成如下格式

作图代码

library(readxl)
library(tidyverse)
library(ggplot2)
library(plotrix)

fig4c2.df<-read_excel("data/20230207/ggplot2barplot.xlsx",
                      sheet = "fig4c2")
fig4c2.df
fig4c2.df %>% 
  rowwise() %>% 
  mutate(mean_value=mean(c_across(rep01:rep03)),
         sde_value=std.error(c_across(rep01:rep03)),
         x=factor(x,levels = x)) -> fig4c2.df01

ggplot(data=fig4c2.df01,aes(x=x,y=mean_value))+
  geom_errorbar(aes(ymin=mean_value-sde_value,
                    ymax=mean_value+sde_value),
                width=0.2)+
  geom_col(aes(fill=x),alpha=0.5,color="black")+
  geom_jitter(data=fig4c2.df %>% pivot_longer(!x),
              aes(x=x,y=value,fill=x),size=5,
              shape=21,
              stroke=0.3,
              color="gray")+
  scale_fill_manual(values = c("#094cc3","#f68a15","#008c00"))+
  theme_classic()+
  scale_y_continuous(expand = expansion(mult=c(0,0)),
                     limits = c(0,45))+
  annotate(geom = "segment",x=1,xend = 2,y=43,yend=43,size=2,color="red")+
  annotate(geom = "segment",x=1,xend = 1,y=43,yend=35,size=2,color="red")+
  annotate(geom = "text",x=1.5,y=44,label="***",size=10,color="black")+
  annotate(geom = "segment",x=1,xend = 3,y=33,yend=33,size=2,color="red")+
  annotate(geom = "segment",x=1,xend = 1,y=33,yend=28,size=2,color="red")+
  annotate(geom = "text",x=2.8,y=34,label="**",size=10,color="black")+
  theme(legend.position = "none")+
  labs(x=NULL,y=expression(paste("Percentage of body ",weight%+-%s.e.m)))

这里遇到一个问题是expression表达式中如何换行，之前好像查过，但是想不起来在哪了

在来个figure2q

论文中提供的数据如下

手动整理成如下格式

作图代码

library(ggh4x)
fig2q.df<-read_excel("data/20230207/ggplot2barplot.xlsx",
                      sheet = "fig2q")
fig2q.df
fig2q.df %>% 
  mutate(Replicate=factor(Replicate,levels=rev(Replicate))) %>% 
  rowwise() %>% 
  mutate(mean_value=mean(c_across(rep01:rep06)),
         sde_value=std.error(c_across(rep01:rep06))) -> fig2q.df.01

ggplot(data=fig2q.df.01,aes(x=mean_value,y=Replicate))+
  geom_errorbarh(aes(xmin=mean_value-sde_value,
                     xmax=mean_value+sde_value),
                 height=0.2)+
  geom_col(aes(fill=Replicate),color="black")+
  scale_x_continuous(expand = expansion(mult=c(0,0)),
                     limits = c(0,0.012),
                     breaks = c(0,0.006,0.012),
                     guide = "axis_minor",
                     minor_breaks = seq(0.0006,0.012,by=0.0006))+
  theme_classic()+
  geom_jitter(data=fig2q.df %>% 
                mutate(Replicate=factor(Replicate,levels=rev(Replicate))) %>% 
                pivot_longer(!Replicate),
              aes(y=Replicate,x=value),
              shape=21,stroke=.3,
              color="gray",
              size=5,fill="gray")+
  scale_y_discrete(labels=c("MRT67307","GW6741","Vehicle","Vehicle"))+
  labs(y=NULL,x="Fabp1 mRNA levels + s.e.m")+
  theme(legend.position = "none",
        plot.margin = unit(c(0.1,1,0.1,0.1),'cm'),
        ggh4x.axis.ticks.length.minor= rel(0.5),
        axis.ticks.length.x = unit(0.5,'lines'))+
  scale_fill_manual(values = rev(c("#d2d2d2","#d07112","#3fab35","#ae2886"))) -> p2
    

ggplot()+
  annotate(geom="segment",x=1,xend=1,y=1,yend=3.4,size=3,color="#cf7113")+
  annotate(geom = "text",x=1,y=2,label="FA 800 uM",angle=90,vjust=-1)+
  annotate(geom="segment",x=1,xend=1,y=3.6,yend=4.5,size=3,color="black")+
  annotate(geom = "text",x=1,y=4,label="BSA",angle=90,vjust=-1)+
  theme_void() -> p3

ggplot()+
  annotate(geom="segment",x=1,xend=1,y=1,yend=3,size=3,color="red")+
  annotate(geom = "text",x=1,y=2,label="P = 0.034",angle=90,vjust=1.5)+
  annotate(geom="segment",x=1.5,xend=1.5,y=2,yend=3,size=3,color="red")+
  annotate(geom = "text",x=1.5,y=2.5,label="P = 0.039",angle=90,vjust=1.5)+
  annotate(geom="segment",x=1.25,xend=1.25,y=3,yend=4,size=3,color="red")+
  annotate(geom = "text",x=1.25,y=3.5,label="P = 0.001",angle=90,vjust=1.5)+
  theme_void()+xlim(1,2) -> p4

library(patchwork)
p3+p2+p4+
  plot_layout(widths = c(1,8,1))

最后是将两个图组合到一起

library(patchwork)
p3+p2+p4+
  plot_layout(widths = c(1,8,1)) -> p324


p1 + p324

示例数据和代码可以给推文点赞，然后点击在看，最后留言获取

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