跟着Nature Communications学作图：R语言ggplot2平滑曲线折线图

用户7010445

发布于 2023-01-06 18:39:06

2K0

发布于 2023-01-06 18:39:06

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

A highly conserved core bacterial microbiota with nitrogen-fixation capacity inhabits the xylem sap in maize plants

https://www.nature.com/articles/s41467-022-31113-w

本地pdf s41467-022-31113-w.pdf

数据代码链接

https://github.com/PlantNutrition/Liyu

今天的推文我们重复一下论文中的Figure2e

image.png

关于平滑曲线，之前的推文有过介绍，可以参考

我们看下这个论文里是用什么代码来实现的

示例数据集部分截图

image.png

读取数据

top_genus <- read.delim("data/20220616/top_genus.txt",
                       header=T, 
                       row.names=1, 
                       sep="\t",
                       stringsAsFactors = FALSE,
                       check.names = FALSE)

赋予因子水平

top_genus$Genus<-factor(
  top_genus$Genus,
  levels=c("Bacillus","Cronobacter",
           "Unclassified_Enterobacterales",
           "Klebsiella","Pantoea",
           "Pseudomonas","Rosenbergiella"), 
  labels = c("Bacillus","Cronobacter",
             "Unclassified_Enterobacterales",
             "Klebsiella","Pantoea",
             "Pseudomonas","Rosenbergiella"))

准备配色

phy.cols <- c("#85BA8F", "#A3C8DC",
              "#349839","#EA5D2D",
              "#EABB77","#F09594","#2072A8")

普通折线图的代码

library(ggplot2)
p=ggplot(data=top_genus,
         aes(x=Compartment,y=RA,
             group=Genus,colour=Genus))+
  geom_point(size=3)+
  labs(x="Compartments", y="Relative abundance (%)")+
  geom_line()+
  scale_x_discrete(limits=c("RS","RE","VE","SE","LE","P","BS"))+
  scale_colour_manual(values=phy.cols) 
p

image.png

论文中提供的代码没有用BS的数据，所以会有警告信息

image.png

平滑曲线他用到的是 ggalt包中的 geom_xspline函数

library(ggalt)
p2<-ggplot(data=top_genus,aes(x=Compartment,y=RA,
                              group=Genus,colour=Genus))+
  geom_point(size=3)+
  labs(x="Compartments", y="Relative abundance (%)")+
  geom_xspline(spline_shape = -0.5)+
  scale_x_discrete(limits=c("RS","RE","VE","SE","LE","P"))+
  scale_colour_manual(values=phy.cols) 
p2

image.png

拼图

mytheme = theme_bw() +
  theme(axis.text.x = element_text(size = 8),axis.text.y = element_text(size = 8))+
  theme(axis.title.y= element_text(size=12))+theme(axis.title.x = element_text(size = 12))+
  theme(legend.title=element_text(size=5),legend.text=element_text(size=5))+theme(legend.position = "bottom")


library(patchwork)

p+mytheme + p2 + mytheme +
  plot_layout(guides = "collect")+
  plot_annotation(theme = theme(legend.position = "bottom"))

image.png

示例数据和代码可以到论文中去下载

本文参与腾讯云自媒体同步曝光计划，分享自微信公众号。

原始发表：2022-06-16，如有侵权请联系 cloudcommunity@tencent.com 删除

https

网络安全

本文分享自小明的数据分析笔记本微信公众号，前往查看

如有侵权，请联系 cloudcommunity@tencent.com 删除。

本文参与腾讯云自媒体同步曝光计划，欢迎热爱写作的你一起参与！

https

网络安全

登录后参与评论

0 条评论

热度