将变量函数标签添加到R中的三元图

问题描述

我想将我的数据绘制为三元图，其中基因在三种条件之一（即）下上升或下降。更接近显示更高值的条件。

1. 是否为每个变量标准化了独立于值的值？
2. 我可以在选定的声明变量“ func2”的“基因”变量中添加标签吗？

这是我获得的（顶部）和我想要的（底部）的可复制示例。

gene <- c("Gene1","Gene2","Gene3","Gene4","Gene5","Gene6")
func1 <- c("A","B","C","D","A")
func2 <- c("A1","B1","C1","D1","C2","A2")
Cond1 <- c(0.007623561,0.004639893,0.000994121,0.017494429,0.000366445,0.006663334)
Cond2 <- c(0.011299941,0.009994388,0.001012428,0.013695669,0.000299771,0.010287904)
Cond3 <- c(0.005055458,0.016826251,0.001311254,0.016115009,0.000242897,0.004583889)
df <- data.frame(gene,func1,func2,Cond1,Cond2,Cond3)


library(ggplot2) 
library(ggtern) 
ggtern(data=df,aes(x=Cond1,y=Cond2,z=Cond3,color=func1)) +
theme_bw() +
geom_point() +
labs(x="Cond1",y="Cond2",z="Cond3") +
scale_T_continuous(breaks=unique(df$x))+ 
scale_L_continuous(breaks=unique(df$y))+ 
scale_R_continuous(breaks=unique(df$z))

解决方法

我们首先存储原始图：

library(ggtern)

g = ggtern(data=df,aes(x=Cond1,y=Cond2,z=Cond3,color=func1)) +
theme_bw() +
geom_point() +
labs(x="Cond1",y="Cond2",z="Cond3") +
scale_T_continuous(breaks=unique(df$x))+ 
scale_L_continuous(breaks=unique(df$y))+ 
scale_R_continuous(breaks=unique(df$z))

使用geom_label_viewport()选项，一个简单的带注释的图将如下所示：

g + geom_text(aes(label=func2),hjust=-0.2,vjust=-0.2,size=3)

您可以像这样子集标记点：

g + geom_text(data=~subset(.,func2 %in% c("C2","B1")),aes(label=func2),size=3)