使用计算统计在ggplot2 boxplot中排序x轴

I have some data that I want to display as a box plot using ggplot2. It's basically counts, stratified by two other variables. Here's an example of the data (in reality there's a lot more, but the structure is the same):

我有一些数据要显示为使用ggplot2的方框图。它基本上是重要的，由另外两个变量分层。这是一个数据示例（实际上还有更多，但结构是相同的）：

TAG Count Condition
A     5         1
A     6         1
A     6         1
A     6         2
A     7         2
A     7         2
B     1         1
B     2         1
B     2         1
B    12         2
B     8         2
B    10         2
C    10         1
C    12         1
C    13         1
C     7         2
C     6         2
C    10         2

For each Tag, there are a fixed number of observations in condition 1, and condition 2 (here it's 3, but in the real data it's much more). I want a box plot like the following ('s' is a dataframe arranged as above):

对于每个标签，在条件1和条件2中存在固定数量的观察（这里是3，但在实际数据中它更多）。我想要一个像下面这样的盒子图（'s'是如上排列的数据框）：

ggplot(s, aes(x=TAG, y=Count, fill=factor(Condition))) + geom_boxplot()

This is fine, but I want to be able to order the x-axis by the p-value from a Wilcoxon test for each Tag. For example, with the above data, the values would be (for the tags A,B, and C respectively):

这很好，但我希望能够通过每个Tag的Wilcoxon测试的p值来排序x轴。例如，使用上面的数据，值将是（分别对于标签A，B和C）：

> wilcox.test(c(5,6,6),c(6,7,7))$p.value
[1] 0.1572992
> wilcox.test(c(1,2,2),c(12,8,10))$p.value
[1] 0.0765225
> wilcox.test(c(10,12,13),c(7,6,10))$p.value
[1] 0.1211833

Which would induce the ordering A,C,B on the x-axis (largest to smallest). But I don't know how to go about adding this information into my data (specifically, attaching a p-value at just the tag level, rather than adding a whole extra column), or how to use it to change the x-axis order. Any help greatly appreciated.

这将导致x轴上的排序A，C，B（从最大到最小）。但我不知道如何将这些信息添加到我的数据中（特别是在标签级别附加p值，而不是添加一个额外的列），或者如何使用它来更改x轴订购。任何帮助非常感谢。

1 个解决方案

#1

Here is a way do it. The first step is to calculate the p-values for each TAG. We do this by using ddply which splits the data by TAG, and calculates the p-value using the formula interface to wilcox.test. The plot statement reorders the TAG based on its p-value.

这是一种方法。第一步是计算每个TAG的p值。我们通过使用ddply来实现这一点，ddply通过TAG分割数据，并使用wilcox.test的公式接口计算p值。绘图语句根据其p值重新排序TAG。

library(ggplot2); library(plyr)
dfr2 <- ddply(dfr, .(TAG), transform, 
  pval = wilcox.test(Count ~ Condition)$p.value)

qplot(reorder(TAG, pval), Count, fill = factor(Condition), geom = 'boxplot', 
  data = dfr2)