跟着NatureEcology&Evolution学作图：R语言smplot2画云雨图

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发布于 2023-12-11 14:27:45

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发布于 2023-12-11 14:27:45

文章被收录于专栏：小明的数据分析笔记本小明的数据分析笔记本

论文

The evolution of human altriciality and brain development in comparative context

https://www.nature.com/articles/s41559-023-02253-z

数据代码

https://figshare.com/articles/dataset/The_evolution_of_human_altriciality_and_brain_development_in_comparative_context/22242724

论文中的数据和代码都有，看论文，然后对应数据和代码，应该能更好的理解论文的内容。今天的推文我们复现一下论文中的Figure1bcef 云雨图

这里用到的是smplot2这个R包

对应的github主页是 https://github.com/smin95/smplot2

还有专门的文档介绍这个R包的用法 https://smin95.github.io/dataviz/

读取数据

library(tidyverse)
#devtools::install_github('smin95/smplot2')
library(smplot2)
mammals<-read.table("data/20231205/final_compilation with percentage values.R1.csv",
                    header=T,sep=",",row.names=1)

colnames(mammals)

mammals %>% 
  select(NeoBody,AdultBody,BodyRatio) %>% 
  head()

mammals %>% pull(Order2) %>% table()

mammals %>% pull(Over500gr) %>% table()

ordercolors<-c("coral1","lightslateblue","olivedrab3",
               "goldenrod1","lightgray")
mammals$Order2 <- factor(mammals$Order2, 
                         levels = c("Artiodactyla", "Carnivora", 
                                    "Primates", "Rodentia", "Others"))

mammals$Over500gr<-factor(mammals$Over500gr,
                          levels = c("Perissodactyls","Cetaceans",
                                     "Arctoids","Hominids","Elephants","Others"))

figure1b

ggplot(mammals, aes(x = Order2, y = 100*BodyRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Body Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Artio','Carn','Prim','Rod','Others'))

image.png

这个配色还挺好看的，另外3个图和这个图基本一致，这个R包还挺好用的，一行代码就出这个图

另外3个图的代码

ggplot(mammals, aes(x = Order2, y = 100*BrainRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Brain Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Artio','Carn','Prim','Rod','Others'))


ggplot(mammals %>% 
         filter(Over500gr != "Others"), 
       aes(x = Over500gr, y = 100*BrainRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Brain Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Peeriss','Cet','P&B','Hom','Eleph'))


ggplot(mammals %>% 
         filter(Over500gr != "Others"), 
       aes(x = Over500gr, y = 100*BodyRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Body Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Peeriss','Cet','P&B','Hom','Eleph'))

四个图组合到一起

fig1b<-ggplot(mammals, aes(x = Order2, y = 100*BodyRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Body Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Artio','Carn','Prim','Rod','Others'))

fig1c<-ggplot(mammals, aes(x = Order2, y = 100*BrainRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Brain Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Artio','Carn','Prim','Rod','Others'))

fig1d<-ggplot(mammals %>% 
         filter(Over500gr != "Others"), 
       aes(x = Over500gr, y = 100*BodyRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Body Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Peeriss','Cet','P&B','Hom','Eleph'))

fig1e<-ggplot(mammals %>% 
         filter(Over500gr != "Others"), 
       aes(x = Over500gr, y = 100*BrainRatio, fill = Order2)) + 
  ylim(0,100)+
  labs(y="Brain Proportion (%)",x="")+
  scale_fill_manual(values = ordercolors)+
  sm_raincloud() +
  theme(text = element_text(size = 13))+
  scale_x_discrete(labels = c('Peeriss','Cet','P&B','Hom','Eleph'))

library(patchwork)

fig1b+fig1c+fig1d+fig1e+
  plot_annotation(tag_levels = list(c("b","c","d","e")))