这是一个使用的技巧labeller=label_parsed
.
首先,定义标签df$genes
使用要解析的表达式:
df$genes <- factor(df$genes, levels = c("BA","MLL","pos","neg","PMLalpha+"),
ordered = TRUE, labels=c("BA","MLL","pos","neg",expression(paste("PML", alpha,"+"))))
然后使用labeller=label_parsed
in facet_wrap
:
ggplot(df,aes(x=genes, y=value)) + geom_boxplot() +
facet_wrap(~genes, ncol = 5, scales = "free_x", labeller = label_parsed)
正如您所看到的,这与 x 轴标签混淆,但您可以将其修复scale_x_discrete
如下:
ggplot(df,aes(x=genes, y=value)) + geom_boxplot() +
facet_wrap(~genes, ncol = 5, scales = "free_x", labeller = label_parsed) +
scale_x_discrete(name="",
breaks = c("BA","MLL","pos","neg","paste(\"PML\", alpha, \"+\")"),
labels = c("BA","MLL","pos","neg", expression(paste("PML", alpha,"+"))))
Edit:为了回应发布的后续问题,这里是使用的解决方案label_parsed
对于多个变量。在变量字符串中包含请求的空间。
df$var2 <- c(rep(c('trt a','trt b'), NROW(df)/2),'trt a')
df$var2 <- factor(df$var2, levels=c('trt a','trt b'), ordered=T, labels=c(expression(paste("trt ", alpha)), expression(paste("trt ", beta))))
ggplot(df,aes(x=var2, y=值)) + geom_boxplot() +
facet_wrap(〜var2,ncol = 5,scale =“free_x”,labeller = label_parsed)
修复 x 轴:
ggplot(df,aes(x=var2, y=value)) + geom_boxplot() +
facet_wrap(~var2, ncol = 5, scales = "free_x", labeller = label_parsed) +
scale_x_discrete(name="",
breaks = c(expression(paste("trt ", alpha)), expression(paste("trt ", beta))),
labels = c(expression(paste("trt ", alpha)), expression(paste("trt ", beta))))