近日在《The new england journal o f medicine》雜志看到一篇文章的圖，如下，這種圖應(yīng)該是用GraphPad prism做的，圖的特點(diǎn)是散點(diǎn)統(tǒng)計(jì)圖，仔細(xì)觀察中間還展示了平均值和四分位數(shù)，坐標(biāo)軸也是截?cái)嗟?。這里我們使用R來(lái)做一下。

image.png

（Reference：A Novel Circulating MicroRNA for the Detection of Acute Myocarditis）

示例數(shù)據(jù)及注釋代碼已上傳群文件！

首先讀入數(shù)據(jù)，包含表達(dá)值和分組：

setwd("E:/生物信息學(xué)/ggplot坐標(biāo)軸截?cái)?)
A <- read.csv("Exp.csv", header = T)
library(ggplot2)
library(forcats)
library(ggpubr)
A$GeneSymbol <- as.factor(A$GeneSymbol)
A$GeneSymbol <- fct_inorder(A$GeneSymbol)

計(jì)算四分位數(shù)：

B <- A %>% 
  group_by(GeneSymbol) %>% 
  mutate(upper =  quantile(S100A12, 0.75),
         lower = quantile(S100A12, 0.25),
         mean = mean(S100A12),
         median = median(S100A12))

設(shè)置需要比較的分組：

my_comparisons1 <- list(c("Asymptomatic", "Mild")) 
my_comparisons2 <- list(c("Asymptomatic", "Severe"))
my_comparisons3 <- list(c("Asymptomatic", "Critical"))

ggplot作圖：

p <- ggplot(A, aes(GeneSymbol, S100A12, 
              shape=GeneSymbol, fill=GeneSymbol))+
  geom_jitter(size=3, position = position_jitter(0.2))+
  scale_shape_manual(values = c(21,24,25,22))+
  scale_fill_manual(values=c("grey",
                                 "#0073B5",
                                 "#C9543B",
                                 "#E59F3F"))+
  geom_errorbar(data=B, aes(ymin = lower, 
                            ymax = upper),width = 0.2,size=0.5)+
  stat_summary(fun = "mean",
               geom = "crossbar",
               mapping = aes(ymin=..y..,ymax=..y..),
               width=0.4,
               size=0.3)+
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.line=element_line(colour="black"),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        axis.text.x = element_text(size = 14,angle = 45,
                                   vjust = 1,hjust = 1, 
                                   color = 'black',face="bold"),
        axis.text.y = element_text(size = 12, color = 'black'),
        plot.title = element_text(hjust = 0.5,size=15,face="bold"),
        legend.position = "NA")+
  ggtitle("S100A2")+
  stat_compare_means(method="t.test",hide.ns = F,
                     comparisons =c(my_comparisons1,my_comparisons2,my_comparisons3),
                     label="p.signif",
                     bracket.size=0.8,
                     size=6)

image.png

坐標(biāo)軸截?cái)啵泻芏嗪瘮?shù)可以實(shí)現(xiàn)，這里演示兩種：

install.packages("gg.gap")
library(gg.gap)
gg.gap(plot=p,
       segments=c(5,10),
       ylim=c(0,850),
       tick_width = c(1,100))

還有g(shù)gbreak：

install.packages("ggbreak")
library(ggbreak)

p+scale_y_cut(breaks = 5,
              which = c(1,3),
              scales = c(3,0.5),
              space = 0.1)

image.png

總體可以，像文章中的要做很多數(shù)據(jù)的時(shí)候，可以使用循環(huán)作圖。當(dāng)然了，一般情況還是建議用prism做就可以了，因?yàn)檫€是比較方便！

看完了。覺(jué)得分享有用的話，幫忙點(diǎn)個(gè)贊，分享一下再走唄！

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