1.Genomic insights into the origin, domestication and diversification of Brassica juncea

注：R语言ggplot2画点和连线展示群体间Fst值和群体内Pi值

学习：1.文章的admixture图下面加各种类的实物图片
2.将组间不同多样性差异值可视化在同一张图片上
3.文章图片配色可以学习

image.png

论文中的 Figure2

image.png

a, Geographic distributions of 480 B. juncea accessions. The geographic map was drawn using R ggplot2. b, The maximum-likelihood phylogeny of 390 B. juncea accessions with over 60% genetic components to the group and model-based clustering with K from 2 to 6. The five other Brassicaceae species used to root the phylogenetic tree are shown as a single branch. Branch colors indicate different groups based on the population structure. Scale bars, 5 cm for G1 and G5; 5 mm for G2, G3, G4 and G6. c, PCA plots showing three divergent clades of 390 B. juncea accessions. d, Nucleotide diversity (π), population divergence (FST) and genetic distance (D) across the six groups. The value in each circle represents a measure of nucleotide diversity for each group; values in red on each line indicate pairwise population divergence between groups, while values in black on each line indicate pairwise genetic distances among groups. e, Group-specific LD decay plots.

图片的配色相对比较好看
Figure2d， 将不同的遗传多样性值可视化到同一张图中。
核苷酸多样性（π），种群分化（F圣）和遗传距离（D）横跨六组。每个圆圈中的值表示每个组核苷酸多样性的度量;每行上红色的值表示组之间的成对种群差异，而每行上的黑色值表示组之间的成对遗传距离。
好多有关群体遗传的论文里都有这个图，每一个点是群体内的多样性用pi来衡量，连线表示群体之间的分化程度 用fst来表示

模仿一下 论文中的 Figure2d

构造数据集

pi值数据格式

image.png

image.png

library(readxl)
dfpi<-read_excel("20210913.xlsx",
                 sheet = "Sheet1")
dfpi

添加坐标

dfpi$x<-2*sin(seq(0,300,60)*pi/180)
dfpi$y<-2*cos(seq(0,300,60)*pi/180)

作图

library(ggplot2)

cols<-c("#666116","#232c86","#e6eb49",
        "#f1a3bc","#f48b19","#64bea0")

ggplot()+
  geom_point(data=dfpi,
             aes(x=x,y=y,color=Population),
             size=40,
             show.legend = F)+
  xlim(-2.5,2.5)+ylim(-2.5,2.5)+
  theme_void()+
  geom_text(data=dfpi,aes(x=x,y=y,label=Population),
            vjust=-0.5,
            color="red")+
  geom_text(data=dfpi,aes(x=x,y=y,
                          label=paste0(round(pi_value*1000,2),
                                       '~x~',
                                       '10**-3')),
            vjust=1,
            parse=T,
            color="red")+
  scale_color_manual(values=cols)

image.png

library(tidyverse)

read_excel("20210913.xlsx",
            sheet = "Sheet2") %>% 
  pivot_longer(!pop,
               names_to = "pop2",
               values_to = "Fst",
               values_drop_na = T) -> dffst
merge(dffst,dfpi,by.x="pop",by.y = "Population") %>% 
  select(pop,pop2,Fst,x,y) %>% 
  rename("x1"="x",
         "y1"="y") %>% 
  merge(dfpi,by.x = "pop2",by.y = "Population") %>% 
  select(pop,pop2,Fst,x,y,x1,y1) -> dffst1

将连线和点图结合到一起

ggplot()+
  geom_segment(data=dffst1,
               aes(x=x,y=y,xend=x1,yend=y1),
               size=1,
               lty="dashed")+
  geom_point(data=dfpi,
             aes(x=x,y=y,color=Population),
             size=40,
             show.legend = F)+
  xlim(-2.5,2.5)+ylim(-2.5,2.5)+
  theme_void()+
  geom_text(data=dfpi,aes(x=x,y=y,label=Population),
            vjust=-0.5,
            color="red")+
  geom_text(data=dfpi,aes(x=x,y=y,
                          label=paste0(round(pi_value*1000,2),
                                       '~x~',
                                       '10**-3')),
            vjust=1,
            parse=T,
            color="red")+
  scale_color_manual(values=cols)

image.png

library(ggrepel)

ggplot()+
  geom_segment(data=dffst1,
               aes(x=x,y=y,xend=x1,yend=y1),
               size=1,
               lty="dashed")+
  geom_text_repel(data=dffst1,aes(x=(x+x1)/2,
                                  y=(y+y1)/2,
                                  label=Fst))+
  geom_point(data=dfpi,
             aes(x=x,y=y,color=Population),
             size=40,
             show.legend = F)+
  xlim(-2.5,2.5)+ylim(-2.5,2.5)+
  theme_void()+
  geom_text(data=dfpi,aes(x=x,y=y,label=Population),
            vjust=-0.5,
            color="red")+
  geom_text(data=dfpi,aes(x=x,y=y,
                          label=paste0(round(pi_value*1000,2),
                                       '~x~',
                                       '10**-3')),
            vjust=1,
            parse=T,
            color="red")+
  scale_color_manual(values=cols)

image.png

参考：https://www.jianshu.com/p/6dd1d88e5c76