跟着Nature Metabolism学作图:R语言ggplot2各种各样柱形图(1)

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

加载作图用到的R包

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

首先是最普通的柱形图

figure3m

示例数据集如下

作图代码

fig3m.df<-read_excel("data/20230207/ggplot2barplot.xlsx",
                     sheet = "fig3m")
fig3m.df
ggplot(data=fig3m.df,aes(x=x,y=y))+
  geom_col(fill="#5ab033",color="black")+
  theme_classic()+
  scale_y_continuous(expand = expansion(mult = c(0,0)),
                     limits = c(0,0.5))+
  labs(x=NULL,y="log(FC)")+
  theme(panel.grid.major.y = element_line(),
        axis.text.x = element_text(angle=90,face="italic",
                                   vjust=0.5,hjust=1))

更多的时候会对数值进行排序，从小到大，或者从大到小

fig3m.df %>% 
  arrange(y) %>% 
  mutate(x=factor(x,levels = x)) %>% 
  ggplot(aes(x=x,y=y))+
  geom_col(fill="#5ab033",color="black")+
  theme_classic()+
  scale_y_continuous(expand = expansion(mult = c(0,0)),
                     limits = c(0,0.5))+
  labs(x=NULL,y="log(FC)")+
  theme(panel.grid.major.y = element_line(),
        axis.text.x = element_text(angle=90,face="italic",
                                   vjust=0.5,hjust=1)) -> p1

fig3m.df %>% 
  arrange(desc(y)) %>% 
  mutate(x=factor(x,levels = x)) %>% 
  ggplot(aes(x=x,y=y))+
  geom_col(fill="#5ab033",color="black")+
  theme_classic()+
  scale_y_continuous(expand = expansion(mult = c(0,0)),
                     limits = c(0,0.5))+
  labs(x=NULL,y="log(FC)")+
  theme(panel.grid.major.y = element_line(),
        axis.text.x = element_text(angle=90,face="italic",
                                   vjust=0.5,hjust=1)) -> p2

p1/p2

柱形图除了水平摆放，也可以垂直摆放，我们把作图代码里的x和y对调位置就行，如果数据集里的数据有正有负，那么柱子呈现的就是既有朝上的，又有朝下的

比如这个figure r s

代码

fig3r.df<-read_excel("data/20230207/ggplot2barplot.xlsx",
                     sheet = "fig3r")

fig3r.df %>% 
  mutate(x=factor(x,levels = c("Vcam1","Pecam1","Alcam","Icam1","Gja4","Gja5","F11r"))) %>% 
  ggplot(aes(x,y))+
  geom_col(fill="#ee7770",color="black")+
  geom_text(aes(y=c(-0.01,-0.01,-0.01,-0.01,-0.01,0.01,0.01),
                label=x),
            angle=90,hjust=c(1,1,1,1,1,0,0),
            color=c("#bf1818","#bf1818","#bf1818","#bf1818","black","black","blue"))+
  theme_classic()+
  theme(axis.line.x = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        panel.grid.major.y = element_line(),
        plot.title = element_text(hjust = 0.5))+
  scale_y_continuous(limits = c(-0.25,0.25),
                     breaks = c(-0.25,seq(-0.2,0.2,by=0.1),0.25),
                     expand = expansion(mult = c(0,0)),
                     labels = c("",seq(-0.2,0.2,by=0.1),""))+
  labs(x=NULL,y="log(FC)",title = "Art")

今天的推文就介绍这么多，明天继续

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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