R ggplot2 boxplots - ggpubr stat_compare_means无法正常工作 [英] R ggplot2 boxplots - ggpubr stat_compare_means not working properly

问题描述

我尝试使用 ggplot2 和 ggpubr 包以星号的形式将重要性级别添加到我的箱型图中，但我有很多比较和我只想显示重要的。

我尝试使用选项 hide.ns = TRUE stat_compare_means 中，但很明显不起作用，它可能是 ggpubr 包中的一个错误。

另外，您看到我从成对的 wilcox.test 比较中省略了组PGMC4;我怎么能把这个小组也留给 kruskal.test ？

最后一个问题是重要程度如何工作？由于*在0.05以下显着，**在0.025以下，***在0.01以下ggpubr使用的是什么？它是显示p值还是调整后的p值？如果是后者，调整方法是什么？ BH？

请检查我的MWE以下并

问题是：

1-如何让hide.ns = TRUE工作？

2-如何增加*的大小？

3-如何从kruskal.test比较中排除组？

4- ggpubr使用的*约定是什么，p值是否显示已调整？

非常感谢！ ！

编辑

此外，在做

  stat_compare_means（比较= my.comps，method =wilcox.test，p.adjust.method =BH）
  

我没有获得与

  wilcox.test（Value〜Group，data = mydf.sub）$ p.value 
  

其中mydf.sub是mydf的子集（）给出了2组的比较。

ggpubr在这里做什么？如何计算p.values？

编辑2

请帮忙，该解决方案不必与ggpubr（但它必须与 ggplot2 ），我只需要能够隐藏NS，并使星号的大小，以及一个p值计算与wilcox.test（）+ p.adjust（方法BH）完全相同。

谢谢！

解决方案

您可以尝试以下操作。这个想法是，您可以使用 pairwise.wilcox.test 来计算您自己的统计数据。然后使用 ggsignif 函数 geom_signif
添加预先计算的pvalues。使用 y_position ，您可以放置​​括号，使它们不重叠。

 图书馆（tidyverse）
图书馆（ggsignif）
图书馆（扫帚）
＃您的您想比较的组合列表
 CN < -  combn（levels（mydf $ Group）[ -  9]，2，simplify = FALSE）
＃pvalues。我使用扫帚和整齐，以获得一个不错的格式化数据框。请注意，我关闭了对pvalues的调整。 
 pv < -  tidy（with（mydf [mydf $ Group！=PGMC4，]，pairwise.wilcox.test（Value，Group，p.adjust.method =none）））
＃数据准备
 CN2 < -  do.call（rbind.data.frame，CN）
 colnames（CN2）<  -  colnames（pv）[ -  3] 
＃subset通过合并CN列表
 pv_final<  -  merge（CN2，pv，by.x = c（group2，group1），by.y = c（group1，group2） ）
＃修复订单
 pv_final<  -  pv_final [order（pv_final $ group1），] 
＃set signif level 
 pv_final $ map_signif<  -  ifelse（pv_final $ p。值> 0.05，，ifelse（pv_final $ p.value> 0.01，*，**））
 
＃plot 
 ggplot（mydf，aes（ x =组，y =值，填充=组） = Group），size = 5）+ 
 ylim（-4,30）+ 
 geom_signif（比较= CN，
 y_position = 3:30，annotation = pv_final $ map_signif）+ 
 theme_bw（base_size = 16）
  

参数 vjust ， textsize 和 size 不能正常工作。似乎是最新版本 ggsignif_0.3.0 中的错误。



---

编辑：只显示重要的比较，您可以轻松地对数据集进行子集化。 vjust 和 textsize 正在更新为 ggsignif_0.4.0 和 R版本3.4.1 。您可以尝试 step_increase

<$ p $而不是 y_position p> ＃subset
gr <-pv_final $ p.value <= 0.05
CN [gr]

ggplot（mydf，aes（x = Group，y = Value，fill = Group））+ geom_boxplot（）+
stat_compare_means（data = mydf [mydf $ Group！=PGMC4，]，aes（x = Group，y = Value，fill = （比较= CN [gr]，textsize = 12，vjust = 0.7，
step_increase = 0.12，annotation = pv_final $ map_signif [gr]）+
theme_bw（base_size = 16）


你也可以使用ggpubr。添加：

  stat_compare_means（比较= CN [gr]，method =wilcox.test，label =p.signif ，color =red）
  

p>

I am trying to add significance levels to my boxplots in the form of asterisks using ggplot2 and the ggpubr package, but I have many comparisons and I only want to show the significant ones.

I try to use the option hide.ns=TRUE in stat_compare_means, but it clearly does not work, it might be a bug in the ggpubr package.

Besides, you see that I leave out group "PGMC4" from the pairwise wilcox.test comparisons; how can I leave this group out also for the kruskal.test?

The last question I have is how the significance level works? As in * is significant below 0.05, ** below 0.025, *** below 0.01? what is the convention ggpubr uses? Is it showing p-values or adjusted p-values? If the latter, what's the adjusting method? BH?

Please check my MWE below and this link and this other one for reference

##############################
##MWE
set.seed(5)
#test df
mydf <- data.frame(ID=paste(sample(LETTERS, 163, replace=TRUE), sample(1:1000, 163, replace=FALSE), sep=''),
                   Group=c(rep('C',10),rep('FH',10),rep('I',19),rep('IF',42),rep('NA',14),rep('NF',42),rep('NI',15),rep('NS',10),rep('PGMC4',1)),
                   Value=rnorm(n=163))
#I don't want to compare PGMC4 cause I have only onw sample
groups <- as.character(unique(mydf$Group[which(mydf$Group!="PGMC4")]))
#function to make combinations of groups without repeating pairs, and avoiding self-combinations
expand.grid.unique <- function(x, y, include.equals=FALSE){
    x <- unique(x)
    y <- unique(y)
    g <- function(i){
        z <- setdiff(y, x[seq_len(i-include.equals)])
        if(length(z)) cbind(x[i], z, deparse.level=0)
    }
    do.call(rbind, lapply(seq_along(x), g))
}
#all pairs I want to compare
combs <- as.data.frame(expand.grid.unique(groups, groups), stringsAsFactors=FALSE)
head(combs)
my.comps <- as.data.frame(t(combs), stringsAsFactors=FALSE)
colnames(my.comps) <- NULL
rownames(my.comps) <- NULL
#pairs I want to compare in list format for stat_compare_means
my.comps <- as.list(my.comps)
head(my.comps)
pdf(file="test.pdf", height=20, width=25)
print(#or ggsave()
  ggplot(mydf, aes(x=Group, y=Value, fill=Group)) + geom_boxplot() +
    stat_summary(fun.y=mean, geom="point", shape=5, size=4) +
    scale_fill_manual(values=myPal) +
    ggtitle("TEST TITLE") +
    theme(plot.title = element_text(size=30),
      axis.text=element_text(size=12),
      axis.text.x = element_text(angle=45, hjust=1),
      axis.ticks = element_blank(),
      axis.title=element_text(size=20,face="bold"),
      legend.text=element_text(size=16)) +
  stat_compare_means(comparisons=my.comps, method="wilcox.test", label="p.signif", size=14) + #WHY DOES hide.ns=TRUE NOT WORK??? WHY DOES size=14 NOT WORK???
  stat_compare_means(method="kruskal.test", size=14) #GLOBAL COMPARISON ACROSS GROUPS (HOW TO LEAVE PGMC4 OUT OF THIS??)
)
dev.off()
##############################

The MWE will produce the following boxplots:

The questions would be:

1- How to make hide.ns=TRUE work?

2- How to increase the size of the *?

3- How to exclude a group from the kruskal.test comparison?

4- What is the * convention used by ggpubr, and are the p-values shown adjusted or not?

Many thanks!!

EDIT

Besides, when doing

stat_compare_means(comparisons=my.comps, method="wilcox.test", p.adjust.method="BH")

I do not obtain the same p-values as when doing

wilcox.test(Value ~ Group, data=mydf.sub)$p.value

where mydf.sub is a subset() of mydf for a given comparison of 2 groups.

What is ggpubr doing here? How does it calculate the p.values?

EDIT 2

Please help, the solution does not have to be with ggpubr (but it has to be with ggplot2), I just need to be able to hide the NS and make the size of the asterisks bigger, as well as a p-value calculation identical to wilcox.test() + p.adjust(method"BH").

Thanks!

解决方案

You can try following. The idea is that you calculate the stats by your own using pairwise.wilcox.test. Then you use the ggsignif function geom_signif to add the precalculated pvalues. With y_position you can place the brackets so they don't overlap.

library(tidyverse)
library(ggsignif)
library(broom)
# your list of combinations you want to compare
CN <- combn(levels(mydf$Group)[-9], 2, simplify = FALSE)
# the pvalues. I use broom and tidy to get a nice formatted dataframe. Note, I turned off the adjustment of the pvalues. 
pv <- tidy(with(mydf[ mydf$Group != "PGMC4", ], pairwise.wilcox.test(Value, Group, p.adjust.method = "none")))
#  data preparation 
CN2 <- do.call(rbind.data.frame, CN)
colnames(CN2) <- colnames(pv)[-3]
# subset the pvalues, by merging the CN list
pv_final <- merge(CN2, pv, by.x = c("group2", "group1"), by.y = c("group1", "group2"))
# fix ordering
pv_final <- pv_final[order(pv_final$group1), ] 
# set signif level
pv_final$map_signif <- ifelse(pv_final$p.value > 0.05, "", ifelse(pv_final$p.value > 0.01,"*", "**"))  

# the plot
ggplot(mydf, aes(x=Group, y=Value, fill=Group)) + geom_boxplot() +
  stat_compare_means(data=mydf[ mydf$Group != "PGMC4", ], aes(x=Group, y=Value, fill=Group), size=5) + 
  ylim(-4,30)+
  geom_signif(comparisons=CN,
              y_position = 3:30, annotation= pv_final$map_signif) + 
  theme_bw(base_size = 16)

The arguments vjust, textsize, and size are not properly working. Seems to be a bug in the latest version ggsignif_0.3.0.

---

Edit: To show only the significant comparisons, you easily can subset the datasets. vjust and textsize are working now as I updated to ggsignif_0.4.0 and R version 3.4.1. Instead of y_position you can als try step_increase

# subset 
gr <- pv_final$p.value <= 0.05
CN[gr]

ggplot(mydf, aes(x=Group, y=Value, fill=Group)) + geom_boxplot() +
  stat_compare_means(data=mydf[ mydf$Group != "PGMC4", ], aes(x=Group, y=Value, fill=Group), size=5) + 
  geom_signif(comparisons=CN[gr], textsize = 12, vjust = 0.7, 
             step_increase=0.12, annotation= pv_final$map_signif[gr]) + 
  theme_bw(base_size = 16)

You can use ggpubr as well. Add:

stat_compare_means(comparisons=CN[gr], method="wilcox.test", label="p.signif", color="red")

这篇关于R ggplot2 boxplots - ggpubr stat_compare_means无法正常工作的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！