跟着nature学绘图之特殊主题热图

R语言数据分析指南

发布于 2022-12-20 19:56:17

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发布于 2022-12-20 19:56:17

文章被收录于专栏：R语言数据分析指南R语言数据分析指南

❝本节来复现「nature medicine」上的一张图，此图也属于热图其主要就是左侧文本框的绘制，小编稍微写了一些代码不够完善有更高需求的可以在此基础上进行进一步的拓展；

原文

❝Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes❞

加载R包

library(tidyverse)
library(readxl)
library(ggh4x)
library(grid)
library(cowplot)

数据清洗

df <- read_excel("41591_2022_2116_MOESM4_ESM.xlsx") %>%
  pivot_longer(-c(ID,group))

定义因子

df$ID <- factor(df$ID,levels = df$ID %>% unique() %>% rev())

数据可视化

此处主要使用了ggh4x包中的一些参数来进行细节的调整

df %>% 
  ggplot(aes(name,ID))+
  geom_tile(color="grey70",fill="white",size=0.3)+
  geom_point(data=df %>% filter(value > 0.08),
             aes(size=abs(value),color=value),shape=15,size=6)+
  scale_color_gradient2(low="grey",mid="grey",high="black")+
  facet_grid2(vars(group),scale="free_y",switch = "y",
              labeller = label_wrap_gen())+
              # 定义分面列宽与行高
  force_panelsizes(cols=c(1.5),rows = c(0.55,0.15,1,0.15,0.9,1.2,0.55,0.15,0.15,0.15),
                   respect = TRUE)+
  scale_y_discrete(expand=c(0,0),position = 'left')+
  scale_x_discrete(expand=c(0,0),position = 'top')+
  labs(x=NULL,y=NULL)+
  theme(panel.background = element_blank(),
        axis.text.x = element_text(color="black",size=8),
        axis.text.y=element_text(color="black"),
        legend.title = element_blank(),
        axis.ticks = element_blank(),
        strip.placement = 'outside',
        strip.text.y.left = element_text(size=8,color="black",face = "bold",angle = 0),
        panel.spacing.y = unit(0,"cm"))+
  guides(color=guide_colorbar(direction = "vertical",
                              reverse=F,barwidth=unit(.5,"cm"),
                              barheight=unit(21,"cm")))+
  coord_cartesian(clip='off')