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我有一个示例数据框：

输入（数据）

structure(list(DAF = c(0.00704225, 0.00352113, 0.00352113, 0.028169, 
0.00352113, 0.00704225, 0.0105634, 0.00352113, 0.0105634, 0.00352113, 
0.00352113, 0.00352113, 0.0176056, 0.0140845, 0.00352113, 0.0140845, 
0.00352113, 0.0105634, 0.00352113, 0.00352113, 0.0140845, 0.00352113, 
0.084507, 0.00352113, 0.0669014, 0.00704225, 0.00352113, 0.00352113, 
0.00704225, 0.00352113, 0.00704225, 0.00352113, 0.00352113, 0.028169, 
0.00352113, 0.00704225, 0.0105634, 0.00352113, 0.0105634, 0.00352113, 
0.00352113, 0.00352113, 0.0176056, 0.0140845, 0.00352113, 0.0140845, 
0.00352113, 0.0105634, 0.00352113, 0.00352113, 0.0140845, 0.00352113, 
0.084507, 0.00352113, 0.0669014, 0.00704225, 0.00352113, 0.00352113, 
0.00704225, 0.00352113), TYPE = structure(c(2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("All SVs", "bDEL"), class = "factor"), 
Function = structure(c(2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
2L, 2L, 2L, 2L, 2L, 1L), .Label = c("Genic", "Intergenic"
), class = "factor")), .Names = c("DAF", "TYPE", "Function"
), class = "data.frame", row.names = c(NA, -60L))

我已经绘制使用“

p1<-ggplot(sv,aes(x=DAF,y=..density..,fill=Function))+geom_histogram(position="dodge",binwidth=0.02)+facet_wrap( ~ TYPE, scales = "free",ncol=2)

数据框中的注释文本：

> dput(dat)
structure(list(x = c(0.05, 0.05, 0.05, 0.05, 0.05, 0.05), y = c(20L, 
17L, 14L, 35L, 30L, 25L), labs = structure(c(3L, 4L, 6L, 1L, 
2L, 5L), .Label = c("mean=0.0173", "mean=0.0190", "mean=0.0415", 
"mean=0.0440", "p=0.0393", "p=1.47e-08"), class = "factor"), 
    TYPE = structure(c(1L, 1L, 1L, 2L, 2L, 2L), .Label = c("All SVs", 
    "bDEL"), class = "factor")), .Names = c("x", "y", "labs", 
"TYPE"), class = "data.frame", row.names = c(NA, -6L))


p2<-p1+geom_text(aes(x, y, label=labs),size=1,data=dat,inherit.aes = F)

这给出了以下情节：

在此处输入图像描述

但是，我需要用图例的相应颜色为每个方面内的文本“mean=...”着色。即在所有 SV 方面，“均值 = 0.0415”应为“基因”颜色，“均值 = 0.0440”应为“基因间”颜色。

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1 回答 1

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您需要在“dat”中添加一列来表示每行/标签应该在哪个组中。我用于NAp 值。

dat$Function = c("Genic", "Intergenic", NA, "Genic", "Intergenic", NA)

然后您可以将此变量映射到colorin geom_text。您可以避免NA使用show.legend = FALSE.

p1 + geom_text(aes(x, y, label = labs, color = Function), 
               size = 1, data = dat, inherit.aes = FALSE, show.legend = FALSE)

NA颜色默认为grey50，如果需要，您可以将其更改为其他颜色scale_color_discrete。

p1 + geom_text(aes(x, y, label = labs, color = Function), 
               size = 1, data = dat, inherit.aes = FALSE, show.legend = FALSE) +
    scale_color_discrete(na.value = "black")
于 2016-11-07T21:02:58.077 回答