论文
Pan-African genome demonstrates how population-specific genome graphs improve high-throughput sequencing data analysis
https://www.nature.com/articles/s41467-022-31724-3
本地pdf s41467-022-31724-3.pdf
论文中公布了大部分图的数据,但是没有公布对应的作图代码,没有关系,我们可以自己写代码试着模仿,今天的推文重复一下论文中的Figure 2A 带有条纹的分组柱形图
示例数据截图
image.png这里实现条纹柱形图用到的是 ggpattern
这个R包
参考链接
https://coolbutuseless.github.io/package/ggpattern/index.html
https://github.com/coolbutuseless/ggpattern
安装
remotes::install_github("coolbutuseless/ggpattern")
因为是ggplot2的扩展包,除了把作图函数替换,其余的细节都可以用ggplot2的语法来调节
读取数据
library(readxl)
dffig2a<-read_excel("data/20220806/41467_2022_31724_MOESM4_ESM.xlsx",
sheet = "figure 2a")
dffig2a
library(tidyverse)
dffig2a %>%
pivot_longer(-'Super-population') -> new.dffig2a
作图代码
library(ggplot2)
cols<-c("#ffa657","#fd8011","#6cbe6c","#349734",
"#eba0d5","#da7dbd","#63a0cb","#1f7ab4",
"#d0d166","#bbbe21")
ggplot(data = new.dffig2a,aes(x=`Super-population`,y=value))+
geom_bar_pattern(stat="identity",
position = "dodge",
aes(pattern=name,
fill=name),
pattern_density=0.01,
fill=cols,
color="black",
show.legend = FALSE)+
scale_pattern_manual(values = c('Divergence'='stripe',
'Diversity'="none"))+
scale_y_continuous(expand = expansion(mult = c(0,0.1)),
labels = scales::percent,
limits = c(0,0.25/100),
breaks = seq(0,0.25/100,by=0.05/100))+
labs(x=NULL,y=NULL)+
theme_classic()+
theme(axis.line.y = element_blank(),
axis.ticks.y = element_blank(),
panel.grid = element_line(linetype = "dashed"),
panel.grid.major = element_line(),
panel.grid.minor = element_blank()) -> p1
p1
ggplot()+
geom_rect_pattern(data=data.frame(x=1,xend=2,y=1,yend=2),
aes(xmin=x,ymin=y,xmax=xend,ymax=yend),
pattern_density=1,
fill="white",
color="black")+
geom_rect_pattern(data=data.frame(x=1,xend=2,y=2.5,yend=3.5),
aes(xmin=x,ymin=y,xmax=xend,ymax=yend),
pattern="none",
pattern_density=1,
fill="grey",
color="black")+
theme_void()+
geom_text(data=data.frame(x=2,y=1.5),
aes(x=x,y=y),label="Divergence",
hjust=-0.1)+
geom_text(data=data.frame(x=2,y=3),
aes(x=x,y=y),label="Diversity",
hjust=-0.1)+
xlim(1,4) -> p2
p1+
annotation_custom(grob = ggplotGrob(p2),
xmin = 4,xmax = Inf,
ymin = 0.2/100,ymax=0.25/100) -> p3
p3
library(patchwork)
p3+p3
image.png
示例数据可以在论文中去下载,代码直接在推文中复制,如果需要我整理好的数据和代码可以给推文打赏1元获取
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