跟着Nature Metabolism學作圖:R語言ggplot2各種各樣柱形圖(1)

論文

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 作圖的數據都有，可以試着用論文中提供的數據復現一下論文中的圖

論文中figure2和figure3中有很多種柱形圖，爭取把每個種類的柱形圖都復現一下

加載作圖用到的R包

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

首先是最普通的柱形圖

figure3m

示例數據集如下

作圖代碼

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))

更多的時候會對數值進行排序，從小到大，或者從大到小

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

柱形圖除了水平擺放，也可以垂直襬放，我們把作圖代碼裏的x和y對調位置就行，如果數據集裏的數據有正有負，那麼柱子呈現的就是既有朝上的，又有朝下的

比如這個figure r s

代碼

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")

今天的推文就介紹這麼多，明天繼續

示例數據和代碼可以給推文點贊，然後點擊在看，最後留言獲取

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