跟着Nature Plants学作图：R语言ggforce做甜甜圈饼图展示基因组中转座子的比例

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发布于 2023-11-03 15:31:41

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发布于 2023-11-03 15:31:41

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

Somatic variations led to the selection of acidic and acidless orange cultivars

https://www.nature.com/articles/s41477-021-00941-x

柑橘体细胞变异2021NP.pdf

今天的推文我们来复现一下论文中的Figure4a

image.png

里面的饼图是三类转座子的一个比例，外面一圈是再进一步分类的转座子的比例

这个用R包ggforce里面的geom_arc_bar()函数很容易实现

首先是构造作图数据

library(ggforce)

dat01<-data.frame(x=c("A","B","D"),
                  y=c(52.3,38.5,9.2))

dat02<-data.frame(x=c('a','b','c','d','e','f','g','h','i'),
                  y=c(26.7,22.9,2.7,30.5,3.9,2,2.1,8.3,0.9))

作图代码

ggplot()+
  geom_arc_bar(data=dat01,
               stat="pie",
               aes(x0=0,y0=0,r0=0,r=2,
                   amount=y,fill=x),
               show.legend = FALSE,
               linewidth=2)+
  theme_bw()+
  theme(panel.grid = element_blank(),
        panel.border = element_blank(),
        axis.title = element_blank(),
        axis.text = element_blank(),
        axis.ticks = element_blank())+
  coord_equal()+
  scale_fill_manual(values = c("white","white","white"))+
  annotate(geom = "text",x=1,y=0,label="LTR\n52.3%",size=5)+
  annotate(geom = "text",x=-1,y=0,label="DNA\n38.5%",size=5)+
  annotate(geom = "text",x=-0.5,y=1.5,label="LINE and\nSINE",size=5)+
  ggnewscale::new_scale_fill()+
  geom_arc_bar(data=dat02,
               stat="pie",
               aes(x0=0,y0=0,r0=2.1,r=3.1,
                   amount=y,fill=x),
               show.legend = FALSE,
               linewidth=0.5)+
  annotate(geom = "text",x=1.8,y=1.9,label="Gypsy\n26.7%",size=5)+
  annotate(geom = "text",x=1.6,y=-1.9,label="Copia\n22.9%",size=5)+
  annotate(geom = "text",x=-0.15,y=-2.5,label="LTR\nothers\n1.7%",size=3)+
  annotate(geom = "text",x=-2.4,y=-1,label="MuLE\n30.5%",size=5)+
  annotate(geom = "text",x=-2.1,y=1.5,label="hAT\n3.9%",size=5)+
  annotate(geom = "text",x=-2.6,y=2.3,label="CMC-EnSpm\n2.0%",size=5)+
  annotate(geom = "text",x=-2.3,y=2.7,label="DNA others\n2.1%",size=5)+
  annotate(geom = "text",x=-0.8,y=2.5,label="Line\n8.3%",size=5)+
  annotate(geom = "text",x=0,y=3.3,label="SINE 9%",size=5)+
  scale_fill_manual(values = c("#ffe699","#c6deb5","#c7c7c7","#ff9999",
                               "#99ffff","#f8cbad","#c6acd9","#99dff9","#ffc2ff"))