跟着BMC Plant Biology学作图：R语言ggtree圆形树形图并添加分组背景色

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论文

Comparative analysis of de novo genomes reveals dynamic intra‑species divergence of NLRs in pepper

数据和代码

https://github.com/sdaf11111/NLR-map-in-pepper

论文中Figure2的示例数据和代码作者放到了github主页，我们可以学习一下他的代码

示例数据是一个nwk格式的树文件和一个csv格式的分组文件

学到的新知识点

R包 svglite 输出图片如果保存为svg格式可能会用到这个R包

函数split()可以把数据框根据某一列分组转换成列表格式，文字表达可能有点看不明白，看一下函数的输出效果

df<-data.frame(x=c("A","A","B","B","B"),
               y=c(1,4,5,2,7))
df
split(df$y,df$x)

image.png

函数geom_abline() ggtree里的函数，可以把树末端补平

接下来是实际的代码

首先是加载需要用到的R包

library(dplyr)
library(ggtree)
library(ggplot2)
library(svglite)
library(scales)

读取数据

info <- read.csv("data/20230202/Annuum.Intact.NBARC.group.trimal92.csv")
head(info)
tree <- read.tree("data/20230202/Annuum.Intact.NBARC.tree.trimal92.nwk.txt")

给树添加分组信息

groupInfo<-split(info$ID,info$Group)
tree<- groupOTU(tree, groupInfo)

指定颜色

heatmap.colours <- c("#be9fe1","#8ac6d1","#e1ccec","#fddb3a",
                     "#C0C0C0","#c9b6e4","#d5c455","#ffb6b9","#fae3d9",
                     "#9aceff","#d7cde6","#bbded6","#ede59a","#4f98ca",
                     "#4a69bb","#f5cdaa","NA",
                     "#c3d14a","#63b637","#FF0000","#008000","#FF1493","#FF4500")
names(heatmap.colours) <- c("G1","G2","G3","G4",
                            "G5","G6","G7","G8","G9",
                            "G10","G11","G12","G13","GT",
                            "GR","G14","NG",
                            "CHIL","Know","CANN","CECW","CZUN","CASF")

作图代码

p <- ggtree(tree, layout='circular', size=0.2) %<+% info +
  geom_aline(linetype="solid", 
             size=0.5, aes(color=group),
             alpha=0.5) +   
  scale_colour_manual(values=heatmap.colours,
                      breaks=c("G1","G2","G3","G4","G5",
                               "G6","G7","G8","G9","G10",
                               "G11","G12","G13","GT","GR",
                               "G14","CHIL","Know","CANN",
                               "CECW","CZUN","CASF"), 
                      name="Group") +
  theme(legend.position="right")+
  geom_tippoint(aes(color=Species), size=0.2)+
  guides(color=guide_legend(ncol=6))
q <- flip(p, 3001, 4090) %>% rotate(3507)

ggsave(file="NLR_tree.92.pdf", plot=q,
       width = 9.4,height = 4)

image.png

这里有一个问题是geom_abline()函数的效果如果是在Rstudio的图片显示界面是看不到的，如果保存为pdf就可以看到效果。暂时不明白是什么原因

论文中提供的代码还有一部分是计算MRCA，这部分我暂时没有想明白，想明白了再来介绍吧