【R语言】绘制误差线图+数据分布+显著性分析

写在前面
绘制一个生物学研究中最普遍的图，误差线图+数据分布+显著性分析。

数据准备

自行编写一个数据集，无实际意义。

options(stringsAsFactors = F)
rm(list=ls())
#创建数据集
vec <- c("N","P","Q")
dff <- data.frame()
for(i in 1:length(vec)){
  df <- data.frame(group=vec[i],runif(30))
  dff <- rbind(dff,df)
}
#编写函数计算平均值和标准差
data_summary <- function(data, varname, groupnames){
  require(plyr)
  summary_func <- function(x, col){
    c(mean = mean(x[[col]], na.rm = T),
      sd = sd(x[[col]], na.rm = T))
  }
  data_sum <- ddply(data, groupnames, .fun = summary_func, varname)
  data_sum <- rename(data_sum, c("mean" = varname))
  return(data_sum)
}
#测试函数的功能
df2 <- data_summary(dff, varname = "runif.30.", groupnames = c("group"))
df2$count <- c(30,30,30)
colnames(df2) <- c("group","mean","sd","count")

绘图

p<- ggplot()+ 
  geom_bar(data=df2,mapping=aes(x=group,y=mean), #柱状图
           fill = "white",
           size = 1.5,
           #color = c("#1E90FF","gold","red"),
           position="dodge", # 柱状图格式
           stat="identity", # 数据格式
           width = 0.6)+  # 柱状图尺寸
  geom_jitter(data=dff, #散点
              mapping=aes(x=group,y=runif.30.,fill = group,colour = group,shape = group),
              size = 2,
              height = 0.05,#散点纵向抖动
              
              width = 0.1)+scale_fill_aaas()+ #散点横向抖动
 # scale_color_manual(values = c("#1E90FF","gold","red"))+ #散点颜色
  geom_signif(data=dff,mapping=aes(x=group,y=runif.30.), # 不同组别的显著性
              comparisons = list(c("N", "P"), # 哪些组进行比较
                                 c("N", "Q"),
                                 c("P", "Q")),
              #annotation=c("**"), # 显著性差异做标记
              #map_signif_level=T, # T为显著性，F为直接显示p value
              #tip_length=c(0,0,0,0,0,0), # 修改显著性线两端的长短
              y_position = c(1,1.5,1), # 设置显著性线的位置高度,每个数值代表每个组
              #size=1, # 修改线的粗细
              #textsize = 7, # 修改*标记的大小
              test = "t.test")+ # 检验的类型
  geom_errorbar(data=df2,mapping=aes(x = group,ymin = mean-sd, ymax = mean+sd), # 误差线添加
                width = 0.3, #误差线的宽度
                color = c("black"), #颜色
                size=0.8)+ #粗细
  scale_y_continuous(limits =c(0, 2) ,expand = c(0,0))+ # y轴的范围
  theme_classic(  # 主题设置，这个是无线条主题
    base_line_size = 1 # 坐标轴的粗细
  )+
  labs(title="White blood cell(WBC)",x="",y="Retive_Abundance")+ # 添加标题，x轴，y轴内容
  theme(plot.title = element_text(size = 15,
                                  colour = "black",
                                  hjust = 0.5),
        axis.title.y = element_text(size = 15, 
                                    # family = "myFont", 
                                    color = "black",
                                    face = "bold", 
                                    vjust = 1.9, 
                                    hjust = 0.5, 
                                    angle = 90),
        legend.title = element_text(color="black", # 修改图例的标题
                                    size=15, 
                                    face="bold"),
        legend.text = element_text(color="black", # 设置图例标签文字
                                   size = 10, 
                                   face = "bold"),
        axis.text.x = element_text(size = 13,  # 修改X轴上字体大小，
                                   color = "black", # 颜色
                                   face = "bold", #  face取值：plain普通，bold加粗，italic斜体，bold.italic斜体加粗
                                   vjust = 0.5, # 位置
                                   hjust = 0.5, 
                                   angle = 0), #角度
        axis.text.y = element_text(size = 13,  
                                   color = "black",
                                   face = "bold", 
                                   vjust = 0.5, 
                                   hjust = 0.5, 
                                   angle = 0) 
  )
p

最后出图的效果：

image.png

我选的都是随机数据，没有差异也算是意料之内把。

参考链接：
1.https://mp.weixin.qq.com/s/19yZc8_HDoJ2w-e1h-k58Q
2.https://www.jianshu.com/p/634f6061a9cb
3.https://cloud.tencent.com/developer/article/1692505

后记
我还想做一种图，是把差异的结果用ABCD表示，但是我发现，好像ggplot做不了，找到了一个老哥写的帖子，后面好好学习一下。https://www.jianshu.com/p/e11164ee0577