如何将Spearman相关p值与相关系数相加到ggpairs？ [英] How to add the spearman correlation p value along with correlation coefficient to ggpairs?

问题描述

使用以下代码在R中构造ggpairs图形。

df是一个数据帧，其中包含6个连续变量和一个 Group 变量

  ggpairs（df [，-1]，列= 1：ncol（df [，-1]），
 mapping = ggplot2 :: aes（colour = df $ Group），传说= T，axisLabels =显示，
上层=列表（连续= wrap（ cor，方法=矛兵，大小= 2.5，高度= 0.7）））+ 
主题（面板。 grid.major = element_blank（），panel.grid.minor = element_blank（），
 axis.line = element_line（colour = black））
   
 
 
通常，p值是使用 cor.test 通过 Spearman传递的方法
 
 
 
也知道StackOverFlow讨论中有类似的查询，但是我需要 ggpairs ，但解决方案不是加工。此外，先前的查询尚未解决。 
 
 
 
  
 
 
 
我认为对于您自己的情节来说，文本间距可能不是最佳的，但这只是调整 my_fn 。
 
Constructing a ggpairs figure in R using the following code. 

df is a dataframe containing 6 continuous variables and one Group variable
ggpairs(df[,-1],columns = 1:ncol(df[,-1]),
mapping=ggplot2::aes(colour = df$Group),legends = T,axisLabels = "show", 
upper = list(continuous = wrap("cor", method = "spearman", size = 2.5, hjust=0.7)))+ 
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"))
I am trying to add the p-value of spearman correlation to the upper panel of the figure generated (i.e) appended to the Spearman correlation coefficient. 

Generally, the p-value is computed using cor.test  with method passed as "Spearman"

Also aware of the StackOverFlow post discussion a query similar to this, but I need for ggpairs, for which the solution is not working. Also, the previous query is not solved yet. 

How to add p values for Spearman correlation coefficients plotted using pairs in R
解决方案
I have a feeling this is more than what you expected.. so you need to define a custom function like ggally_cor, so first we have a function that prints the correlation between 2 variables:
printVar = function(x,y){
      vals = cor.test(x,y,
      method="spearman")[c("estimate","p.value")]
      names(vals) = c("rho","p")
      paste(names(vals),signif(unlist(vals),2),collapse="\n")
}
Then we define a function that takes in the data for each pair, and calculates 1. overall correlation, 2. correlation by group, and pass it into a ggplot and basically only print this text:
my_fn <- function(data, mapping, ...){
  # takes in x and y for each panel
  xData <- eval_data_col(data, mapping$x)
  yData <- eval_data_col(data, mapping$y)
  colorData <- eval_data_col(data, mapping$colour)

# if you have colors, split according to color group and calculate cor

  byGroup =by(data.frame(xData,yData),colorData,function(i)printVar(i[,1],i[,2]))
  byGroup = data.frame(col=names(byGroup),label=as.character(byGroup))
  byGroup$x = 0.5
  byGroup$y = seq(0.8-0.3,0.2,length.out=nrow(byGroup))

#main correlation
mainCor = printVar(xData,yData)

p <- ggplot(data = data, mapping = mapping) +
annotate(x=0.5,y=0.8,label=mainCor,geom="text",size=3) +
geom_text(data=byGroup,inherit.aes=FALSE,
aes(x=x,y=y,col=col,label=label),size=3)+ 
theme_void() + ylim(c(0,1))
  p
}
Now I use mtcars, first column is a random Group:
df  =data.frame(
Group=sample(LETTERS[1:2],nrow(mtcars),replace=TRUE),
mtcars[,1:6]
)
And plot:
ggpairs(df[,-1],columns = 1:ncol(df[,-1]),
mapping=ggplot2::aes(colour = df$Group),
axisLabels = "show", 
upper = list(continuous = my_fn))+
theme(panel.grid.major = element_blank(), 
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black")) 


I think for your own plot, the spacing of the text might not be optimal, but it's just a matter of tweaking my_fn .

                        
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