跟着nature communications学绘图(12) ggplot2注释韦恩点图

R语言数据分析指南

发布于 2022-09-21 15:41:15

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发布于 2022-09-21 15:41:15

❝本节来介绍如何绘图韦恩点图及对其进行注释，图表主要使用「ggplot2」,「UpSetR」，「ggplotify」等包来实现，此图我想介绍的重点在于图形格式的转换及拼图下面来进行具体介绍， A highly conserved core bacterial microbiota with nitrogen-fixation capacity inhabits the xylem sap in maize plants ❞

library(tidyverse)
library(UpSetR)
library(ggplotify)
library(cowplot)
library(ggrepel)

otu_RA <- read_tsv("data.xls") %>% column_to_rownames(var="OTUID")

绘制韦恩点图

p1 <- UpSetR::upset(otu_RA, 
              nset = 7, # 集合数
              nintersects = 10, # 绘制交叉数目
              order.by = "freq", # 排序方式
              mb.ratio = c(0.7,0.3), #  条形图与点图之间的比例
              point.size = 1.8,line.size = 1,mainbar.y.label = "Intersection size",
              sets.x.label = "Set Size",
              main.bar.color = "#2a83a2",
              sets.bar.color = "#3b7960",
              queries = list(list(query = intersects,
                                  params = list("BS","RS","RE","VE","SE","LE","P"),
                                  active = T,color="#d66a35",
                                  query.name = "BS vs RS vs RE vs VE vs SE vs LE vs P")))

绘制圈图

p2 <- tribble(~group, ~perc,~A,
        "24%",24,5,
        "76%",76,5) %>% 
  ggplot(aes(A,perc,fill=group))+
  geom_col()+
  coord_polar(theta="y")+
  xlim(0,6)+
  labs(title="Number of overlapped OTUs:1364\nNumber of total OTUs in xylem: 1792")+
  scale_fill_manual(values=c("#75C500","#5686C3"))+
  theme_void()+
  theme(legend.position = "non",
        plot.title = element_text(hjust=0.5,vjust=-62,color="black",size=6.8),
        plot.margin = unit(c(-2,0,-1,0),unit="cm"))+
  geom_text_repel(data=. %>% filter(group=="76%"),
                  aes(label=group,x=5,y=60),
                  nudge_x=-2.5,
                  nudge_y=0,size=4,
                  box.padding = 1,segment.curvature=-0.1,hjust=1)

拼图

p1 %>% as.grob() %>% ggdraw()+
  theme(plot.margin = unit(c(0,0,-0.8,-3),unit="cm"))+
  draw_plot(p2,scale=0.4,x=0.25,y=0.22)

图像导出

ggsave(file="venn.pdf",width=5.6,height=4.3,unit="in",dpi=300)

数据导出

otu_select <- read_tsv("data.xls") %>% filter_all(all_vars(. > 0))

write.table(as.matrix(otu_select),"otu_overlap.txt",sep = '\t',quote = FALSE,col.names = NA)