I would like to plot my data as a ternary plot, where genes go up or down under one of the three conditions, ie. closer to the condition for which shows higher values.
here is a reproducible example of what I obtain (top) and what I want (bottom)
gene <- c("Gene1", "Gene2", "Gene3", "Gene4","Gene5", "Gene6")
func1 <- c("A", "B", "C", "D", "C", "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$z))
We store the original plot first:
library(ggtern)
g = ggtern(data=df,aes(x=Cond1,y=Cond2,z=Cond3,color=func1)) +
theme_bw() +
geom_point() +
labs(x="Cond1",y="Cond2",z="Cond3") +
scale_T_continuous(breaks=unique(df$x))+
scale_L_continuous(breaks=unique(df$y))+
scale_R_continuous(breaks=unique(df$z))
A simple annotated plot will look like this, using the geom_label_viewport()
option:
g + geom_text(aes(label=func2),hjust=-0.2,vjust=-0.2,size=3)
You can subset the points to label like this:
g + geom_text(data=~subset(.,func2 %in% c("C2","B1")),
aes(label=func2),hjust=-0.2,vjust=-0.2,size=3)