Question

跟进this question并为了完整起见，我修改了接受的答案并对结果图进行了自定义，但我仍面临一些重要问题。

总之，我正在做箱形图，反映了Kruskal-Wallis和成对Wilcoxon测试比较的重要性。

我想用星号替换p值数字，只显示重要的比较，将垂直间距减少到最大值。

基本上我想做this，但是由于增加了方面的问题，这会搞砸一切。

到目前为止，我已经开发了一个非常不错的MWE，但它仍然存在问题......

library(reshape2)
library(ggplot2)
library(gridExtra)
library(tidyverse)
library(data.table)
library(ggsignif)
library(RColorBrewer)

data(iris)
iris$treatment <- rep(c("A","B"), length(iris$Species)/2)
mydf <- melt(iris, measure.vars=names(iris)[1:4])
mydf$treatment <- as.factor(mydf$treatment)
mydf$variable <- factor(mydf$variable, levels=sort(levels(mydf$variable)))
mydf$both <- factor(paste(mydf$treatment, mydf$variable), levels=(unique(paste(mydf$treatment, mydf$variable))))

# Change data to reduce number of statistically significant differences
set.seed(2)
mydf <- mydf %>% mutate(value=rnorm(nrow(mydf)))
##

##FIRST TEST BOTH

#Kruskal-Wallis
addkw <- as.data.frame(mydf %>% group_by(Species) %>%
                       summarize(p.value = kruskal.test(value ~ both)$p.value))
#addkw$p.adjust <- p.adjust(addkw$p.value, "BH")
a <- combn(levels(mydf$both), 2, simplify = FALSE)
#new p.values
pv.final <- data.frame()
for (gr in unique(mydf$Species)){
    for (i in 1:length(a)){
        tis <- a[[i]] #variable pair to test
        as <- subset(mydf, Species==gr & both %in% tis)
        pv <- wilcox.test(value ~ both, data=as)$p.value
        ddd <- data.table(as)
        asm <- as.data.frame(ddd[, list(value=mean(value)), by=list(both=both)])
        asm2 <- dcast(asm, .~both, value.var="value")[,-1]
        pf <- data.frame(group1=paste(tis[1], gr), group2=paste(tis[2], gr), mean.group1=asm2[,1], mean.group2=asm2[,2], FC.1over2=asm2[,1]/asm2[,2], p.value=pv)
        pv.final <- rbind(pv.final, pf)
    }
}
#pv.final$p.adjust <- p.adjust(pv.final$p.value, method="BH")
pv.final$map.signif <- ifelse(pv.final$p.value > 0.05, "", ifelse(pv.final$p.value > 0.01,"*", "**"))

cols <- colorRampPalette(brewer.pal(length(unique(mydf$Species)), "Set1"))
myPal <- cols(length(unique(mydf$Species)))

#Function to get a list of plots to use as "facets" with grid.arrange
plot.list=function(mydf, pv.final, addkw, a, myPal){
    mylist <- list()
    i <- 0
    for (sp in unique(mydf$Species)){
        i <- i+1
        mydf0 <- subset(mydf, Species==sp)
        addkw0 <- subset(addkw, Species==sp)
        pv.final0 <- pv.final[grep(sp, pv.final$group1), ]
        num.signif <- sum(pv.final0$p.value <= 0.05)
        P <- ggplot(mydf0,aes(x=both, y=value)) +
            geom_boxplot(aes(fill=Species)) +
            stat_summary(fun.y=mean, geom="point", shape=5, size=4) +
            facet_grid(~Species, scales="free", space="free_x") +
            scale_fill_manual(values=myPal[i]) + #WHY IS COLOR IGNORED?
            geom_text(data=addkw0, hjust=0, size=4.5, aes(x=0, y=round(max(mydf0$value, na.rm=TRUE)+0.5), label=paste0("KW p=",p.value))) +
            geom_signif(test="wilcox.test", comparisons = a[which(pv.final0$p.value<=0.05)],#I can use "a"here
              map_signif_level = F,            
              vjust=0,
              textsize=4,
              size=0.5,
              step_increase = 0.05)
        if (i==1){
            P <- P + theme(legend.position="none",
                  axis.text.x=element_text(size=20, angle=90, hjust=1),
                  axis.text.y=element_text(size=20),
                  axis.title=element_blank(),
                  strip.text.x=element_text(size=20,face="bold"),
                  strip.text.y=element_text(size=20,face="bold"))
        } else{
            P <- P + theme(legend.position="none",
                  axis.text.x=element_text(size=20, angle=90, hjust=1),
                  axis.text.y=element_blank(),
                  axis.ticks.y=element_blank(),
                  axis.title=element_blank(),
                  strip.text.x=element_text(size=20,face="bold"),
                  strip.text.y=element_text(size=20,face="bold"))
        }
        #WHY USING THE CODE BELOW TO CHANGE NUMBERS TO ASTERISKS I GET ERRORS?
        #P2 <- ggplot_build(P)
        #P2$data[[3]]$annotation <- rep(subset(pv.final0, p.value<=0.05)$map.signif, each=3)
        #P <- plot(ggplot_gtable(P2))
        mylist[[sp]] <- list(num.signif, P)
    }
    return(mylist)
}
p.list <- plot.list(mydf, pv.final, addkw, a, myPal)
y.rng <- range(mydf$value)
# Get the highest number of significant p-values across all three "facets"
height.factor <- 0.3
max.signif <- max(sapply(p.list, function(x) x[[1]]))
# Lay out the three plots as facets (one for each Species), but adjust so that y-range is same for each facet. Top of y-range is adjusted using max_signif.
png(filename="test.png", height=800, width=1200)
grid.arrange(grobs=lapply(p.list, function(x) x[[2]] +
             scale_y_continuous(limits=c(y.rng[1], y.rng[2] + height.factor*max.signif))), 
             ncol=length(unique(mydf$Species)), top="Random title", left="Value") #HOW TO CHANGE THE SIZE OF THE TITLE AND THE Y AXIS TEXT?
             #HOW TO ADD A COMMON LEGEND?
dev.off()

它产生以下图：

正如你所看到的，有一些问题，最明显的是：

1 - 着色因某种原因无效

2 - 我似乎无法使用星号更改注释

我想要更像这样的东西（样机）：

所以我们需要：

1 - 让着色工作

2 - 显示星号而非数字

...并获胜：

3 - 制作一个共同的传奇

4 - 将Kruskal-Wallis线置于顶部

5 - 更改标题和y轴文字的大小（和对齐方式）

重要提示

我很感激我的代码尽可能完整，即使它不是最漂亮的，因为我仍然需要使用像“CNb”或“pv.final”这样的中间对象。

解决方案应该很容易转移到其他情况;请考虑单独测试“变量”，而不是“两者”......在这种情况下，我们有6个“刻面”（垂直和水平），一切都变得更加紧张......

我做了另一个MWE：

##NOW TEST MEASURE, TO GET VERTICAL AND HORIZONTAL FACETS

addkw <- as.data.frame(mydf %>% group_by(treatment, Species) %>%
                       summarize(p.value = kruskal.test(value ~ variable)$p.value))
#addkw$p.adjust <- p.adjust(addkw$p.value, "BH")
a <- combn(levels(mydf$variable), 2, simplify = FALSE)
#new p.values
pv.final <- data.frame()
for (tr in levels(mydf$treatment)){
    for (gr in levels(mydf$Species)){
        for (i in 1:length(a)){
            tis <- a[[i]] #variable pair to test
            as <- subset(mydf, treatment==tr & Species==gr & variable %in% tis)
            pv <- wilcox.test(value ~ variable, data=as)$p.value
            ddd <- data.table(as)
            asm <- as.data.frame(ddd[, list(value=mean(value, na.rm=T)), by=list(variable=variable)])
            asm2 <- dcast(asm, .~variable, value.var="value")[,-1]
            pf <- data.frame(group1=paste(tis[1], gr, tr), group2=paste(tis[2], gr, tr), mean.group1=asm2[,1], mean.group2=asm2[,2], FC.1over2=asm2[,1]/asm2[,2], p.value=pv)
            pv.final <- rbind(pv.final, pf)
        }
    }
}
#pv.final$p.adjust <- p.adjust(pv.final$p.value, method="BH")
# set signif level
pv.final$map.signif <- ifelse(pv.final$p.value > 0.05, "", ifelse(pv.final$p.value > 0.01,"*", "**"))
plot.list2=function(mydf, pv.final, addkw, a, myPal){
    mylist <- list()
    i <- 0
    for (sp in unique(mydf$Species)){
    for (tr in unique(mydf$treatment)){
        i <- i+1
        mydf0 <- subset(mydf, Species==sp & treatment==tr)
        addkw0 <- subset(addkw, Species==sp & treatment==tr)
        pv.final0 <- pv.final[grep(paste(sp,tr), pv.final$group1), ]
        num.signif <- sum(pv.final0$p.value <= 0.05)
        P <- ggplot(mydf0,aes(x=variable, y=value)) +
            geom_boxplot(aes(fill=Species)) +
            stat_summary(fun.y=mean, geom="point", shape=5, size=4) +
            facet_grid(treatment~Species, scales="free", space="free_x") +
            scale_fill_manual(values=myPal[i]) + #WHY IS COLOR IGNORED?
            geom_text(data=addkw0, hjust=0, size=4.5, aes(x=0, y=round(max(mydf0$value, na.rm=TRUE)+0.5), label=paste0("KW p=",p.value))) +
            geom_signif(test="wilcox.test", comparisons = a[which(pv.final0$p.value<=0.05)],#I can use "a"here
              map_signif_level = F,            
              vjust=0,
              textsize=4,
              size=0.5,
              step_increase = 0.05)
        if (i==1){
            P <- P + theme(legend.position="none",
                  axis.text.x=element_blank(),
                  axis.text.y=element_text(size=20),
                  axis.title=element_blank(),
                  axis.ticks.x=element_blank(),
                  strip.text.x=element_text(size=20,face="bold"),
                  strip.text.y=element_text(size=20,face="bold"))
        }
        if (i==4){
            P <- P + theme(legend.position="none",
                  axis.text.x=element_text(size=20, angle=90, hjust=1),
                  axis.text.y=element_text(size=20),
                  axis.title=element_blank(),
                  strip.text.x=element_text(size=20,face="bold"),
                  strip.text.y=element_text(size=20,face="bold"))
        }
        if ((i==2)|(i==3)){
            P <- P + theme(legend.position="none",
                  axis.text.x=element_blank(),
                  axis.text.y=element_blank(),
                  axis.title=element_blank(),
                  axis.ticks.x=element_blank(),
                  axis.ticks.y=element_blank(),
                  strip.text.x=element_text(size=20,face="bold"),
                  strip.text.y=element_text(size=20,face="bold"))
        }
        if ((i==5)|(i==6)){
            P <- P + theme(legend.position="none",
                  axis.text.x=element_text(size=20, angle=90, hjust=1),
                  axis.text.y=element_blank(),
                  #axis.ticks.y=element_blank(), #WHY SPECIFYING THIS GIVES ERROR?
                  axis.title=element_blank(),
                  axis.ticks.y=element_blank(),
                  strip.text.x=element_text(size=20,face="bold"),
                  strip.text.y=element_text(size=20,face="bold"))
        }
        #WHY USING THE CODE BELOW TO CHANGE NUMBERS TO ASTERISKS I GET ERRORS?
        #P2 <- ggplot_build(P)
        #P2$data[[3]]$annotation <- rep(subset(pv.final0, p.value<=0.05)$map.signif, each=3)
        #P <- plot(ggplot_gtable(P2))
        sptr <- paste(sp,tr)
        mylist[[sptr]] <- list(num.signif, P)
    }
    }
    return(mylist)
}
p.list2 <- plot.list2(mydf, pv.final, addkw, a, myPal)
y.rng <- range(mydf$value)
# Get the highest number of significant p-values across all three "facets"
height.factor <- 0.5
max.signif <- max(sapply(p.list2, function(x) x[[1]]))
# Lay out the three plots as facets (one for each Species), but adjust so that y-range is same for each facet. Top of y-range is adjusted using max_signif.
png(filename="test2.png", height=800, width=1200)
grid.arrange(grobs=lapply(p.list2, function(x) x[[2]] +
             scale_y_continuous(limits=c(y.rng[1], y.rng[2] + height.factor*max.signif))), 
             ncol=length(unique(mydf$Species)), top="Random title", left="Value") #HOW TO CHANGE THE SIZE OF THE TITLE AND THE Y AXIS TEXT?
             #HOW TO ADD A COMMON LEGEND?
dev.off()

产生以下情节：

现在颜色问题变得更加明显，小平面高度不均匀，并且应该使用冗余小平面条文本来完成。

我被困在这一点上，所以会感激任何帮助。很抱歉这个问题很长，但我认为它几乎就在那里！谢谢！

Answer 1

您可以尝试以下操作。由于您的代码非常繁忙，而且对于我来说太难理解，我建议采用不同的方法。我试图避免循环并尽可能地使用tidyverse。因此，首先我创建了您的数据。然后计算kruskal wallis测试，因为这在ggsignif内是不可能的。之后，我将使用geom_signif绘制所有p.values。最后，将删除无关紧要的内容并增加步骤。

1-使着色工作完成

2-显示星号而不是数字已完成

......胜利：

3-制作一个共同的传奇完成

4-将Kruskal-Wallis线置于顶部完成，我将值置于底部

5-更改标题和y轴文字的大小（和对齐方式）完成

library(tidyverse)
library(ggsignif)

# 1. your data
set.seed(2)
df <- as.tbl(iris) %>% 
  mutate(treatment=rep(c("A","B"), length(iris$Species)/2)) %>% 
  gather(key, value, -Species, -treatment) %>% 
  mutate(value=rnorm(n())) %>% 
  mutate(key=factor(key, levels=unique(key))) %>% 
  mutate(both=interaction(treatment, key, sep = " "))

# 2. Kruskal test
KW <- df %>% 
  group_by(Species) %>%
  summarise(p=round(kruskal.test(value ~ both)$p.value,2),
            y=min(value),
            x=1) %>% 
  mutate(y=min(y))

# 3. Plot  
P <- df %>% 
ggplot(aes(x=both, y=value)) + 
  geom_boxplot(aes(fill=Species)) + 
  facet_grid(~Species) +
  ylim(-3,7)+
  theme(axis.text.x = element_text(angle=45, hjust=1)) +
  geom_signif(comparisons = combn(levels(df$both),2,simplify = F),
              map_signif_level = T) +
  stat_summary(fun.y=mean, geom="point", shape=5, size=4) +
  xlab("") +
  geom_text(data=KW,aes(x, y=y, label=paste0("KW p=",p)),hjust=0) +
  ggtitle("Plot") + ylab("This is my own y-lab")

# 4. remove not significant values and add step increase
P_new <- ggplot_build(P)
P_new$data[[2]] <- P_new$data[[2]] %>% 
  filter(annotation != "NS.") %>% 
  group_by(PANEL) %>%
  mutate(index=(as.numeric(group[drop=T])-1)*0.5) %>% 
  mutate(y=y+index,
         yend=yend+index) %>% 
  select(-index) %>% 
  as.data.frame()
# the final plot  
plot(ggplot_gtable(P_new))

和使用两个方面的类似方法

# --------------------
# 5. Kruskal
KW <- df %>% 
  group_by(Species, treatment) %>%
  summarise(p=round(kruskal.test(value ~ both)$p.value,2),
            y=min(value),
            x=1) %>% 
  ungroup() %>% 
  mutate(y=min(y))


# 6. Plot with two facets  
P <- df %>% 
  ggplot(aes(x=key, y=value)) + 
  geom_boxplot(aes(fill=Species)) + 
  facet_grid(treatment~Species) +
  ylim(-5,7)+
  theme(axis.text.x = element_text(angle=45, hjust=1)) +
  geom_signif(comparisons = combn(levels(df$key),2,simplify = F),
              map_signif_level = T) +
  stat_summary(fun.y=mean, geom="point", shape=5, size=4) +
  xlab("") +
  geom_text(data=KW,aes(x, y=y, label=paste0("KW p=",p)),hjust=0) +
  ggtitle("Plot") + ylab("This is my own y-lab")

# 7. remove not significant values and add step increase
P_new <- ggplot_build(P)
P_new$data[[2]] <- P_new$data[[2]] %>% 
  filter(annotation != "NS.") %>% 
  group_by(PANEL) %>%
  mutate(index=(as.numeric(group[drop=T])-1)*0.5) %>% 
  mutate(y=y+index,
         yend=yend+index) %>% 
  select(-index) %>% 
  as.data.frame()
# the final plot  
plot(ggplot_gtable(P_new))

编辑。

关于p.adjust的{{1}}需求，您可以自行设置功能并直接在geom_signif()内调用。

wilcox.test.BH.adjusted <- function(x,y,n){
  tmp <- wilcox.test(x,y)
  tmp$p.value <- p.adjust(tmp$p.value, n = n,method = "BH")
  tmp
}  

geom_signif(comparisons = combn(levels(df$both),2,simplify = F),
          map_signif_level = T, test = "wilcox.test.BH.adjusted", 
          test.args = list(n=8))

挑战在于知道最终会有多少次独立测试。然后，您可以自己设置n。我在这里使用了8。但这可能是错误的。

Answer 2

一直知道在循环中构造ggplots会产生令人困惑的结果，对于点 1 的解释，我将引用this question和其他许多内容。还有一个关于在现场评估ggplot对象的提示，例如：通过print。重新点 2 ，你很接近，有点调试，试用和错误帮助。以下是plot.list的完整代码：

plot.list=function(mydf, pv.final, addkw, a, myPal){
    mylist <- list()
    i <- 0
    for (sp in unique(mydf$Species)){
        i <- i+1
        mydf0 <- subset(mydf, Species==sp)
        addkw0 <- subset(addkw, Species==sp)
        pv.final0 <- pv.final[grep(sp, pv.final$group1), ]
        num.signif <- sum(pv.final0$p.value <= 0.05)
        P <- ggplot(mydf0,aes(x=both, y=value)) +
            geom_boxplot(aes(fill=Species)) +
            stat_summary(fun.y=mean, geom="point", shape=5, size=4) +
            facet_grid(~Species, scales="free", space="free_x") +
            scale_fill_manual(values=myPal[i]) +
            geom_text(data=addkw0, hjust=0, size=4.5, aes(x=0, y=round(max(mydf0$value, na.rm=TRUE)+0.5), label=paste0("KW p=",p.value))) +
            geom_signif(test="wilcox.test", comparisons = a[which(pv.final0$p.value<=0.05)],#I can use "a"here
                        map_signif_level = F,            
                        vjust=0,
                        textsize=4,
                        size=0.5,
                        step_increase = 0.05)
        if (i==1){
            P <- P + theme(legend.position="none",
                           axis.text.x=element_text(size=20, angle=90, hjust=1),
                           axis.text.y=element_text(size=20),
                           axis.title=element_blank(),
                           strip.text.x=element_text(size=20,face="bold"),
                           strip.text.y=element_text(size=20,face="bold"))
        } else{
            P <- P + theme(legend.position="none",
                           axis.text.x=element_text(size=20, angle=90, hjust=1),
                           axis.text.y=element_blank(),
                           axis.ticks.y=element_blank(),
                           axis.title=element_blank(),
                           strip.text.x=element_text(size=20,face="bold"),
                           strip.text.y=element_text(size=20,face="bold"))
        }
        P2 <- ggplot_build(P)
        P2$data[[4]]$annotation <- rep(subset(pv.final0, p.value<=0.05)$map.signif, each=3)
        P <- ggplot_gtable(P2)
        mylist[[sp]] <- list(num.signif, P)
    }
    return(mylist)
}

请注意，我们无法再通过ggplot语义修改绘图，因为我们已经应用了ggplot_build / ggplot_gtable，因此无法再进行缩放修改。如果要保留它，请在plot.list函数内移动它。所以，改为

grid.arrange(grobs=lapply(p.list, function(x) x[[2]]), 
             ncol=length(unique(mydf$Species)), top="Random title", left="Value")

产量

当然，这不是一个完整的解决方案，但我希望有所帮助。

R ggplot2：具有wilcoxon显着性水平和方面的箱形图。仅显示与星号

2 个答案: