R绘图

R绘图做生物学显著性统计，然后添加显著性标记，但是都是手动，比较繁琐，好在ggplot2有个扩展包ggsignif，提供更加人性化的方法。

参数说明：
y_position： 是短横线在y轴上的高度；
xmin ：为短横线最左端的x轴上的位置；
xmax ：为短横线最右端的x轴上的位置；
tip_length ：短横线下折线的长度；
vjust ：p值或者显著性离短横线的距离，负数在线上，正数在线下；
map_signif_level ：T为显著性，F为p value;
sprintf ：调用C函数sprintf，可以用来格式化字符串。

rm(list = ls())
#调出说明文档
??ggsignif

library(ggplot2)
library(ggsignif)
head(iris)
#自动添加显著性标记
compaired <- list(c("versicolor", "virginica"))
ggplot(iris, aes(x=Species, y=Sepal.Width, fill=Species)) +
  geom_boxplot() +
  geom_signif(comparisons = compaired,
              map_signif_level = T)


#手动添加显著性标记
dat <- data.frame(Group = c("S1","S1","S2","S2"),
                  Sub =  c("A","B","A","B"),
                  Value = c(3,5,7,8))
dat
ggplot(dat, aes(Group, Value)) +
  geom_bar(aes(fill = Sub), stat = "identity", position = "dodge", width = .5) +
  geom_signif(y_position = c(5.3, 8.3), xmin = c(0.8, 1.8), xmax = c(1.2, 2.2),
              annotations = c("**","NS"), tip_length = 0) +
  geom_signif(comparisons = list(c("S1","S2")),
              y_position = 9.3, tip_length = 0, vjust = 0) +
  scale_fill_manual(values = c("grey80","grey20"))

Rplot00.png

??geom_signif
ggplot(mpg, aes(class, hwy, fill= class)) +
  geom_boxplot() +
  geom_signif(comparisons = list(c("compact", "pickup"),
                                 c("subcompact", "suv")))

Rplot03.png

ggplot(mpg, aes(class, hwy, fill= class)) +
  geom_boxplot() +
  geom_signif(comparisons = list(c("compact", "pickup"),
                                 c("subcompact", "suv")),
              map_signif_level = T)

Rplot04.png

ggplot(mpg, aes(class, hwy, fill=class)) +
  geom_boxplot() +
  geom_signif(comparisons = list(c("compact", "pickup"),
                                 c("subcompact", "suv")),
              map_signif_level=function(p)sprintf("p = %.2g", p))

Rplot05.png

ggplot(mpg, aes(class, hwy, fill= class)) +
  geom_boxplot() +
  geom_signif(annotations = c("First", "Second"),
              y_position = c(30, 40), xmin=c(4,1), xmax=c(5,3))

Rplot06.png

据此，将文章R绘图应用实例：成组的t检验及绘图添加显著性做适当修改，参数如下：

ggplot(result_long_count2, aes(x=variable, y=value, fill=Treated)) + 
  geom_bar(position=position_dodge(.9), stat="identity",
           colour="black",size=.3) +  
  geom_errorbar(aes(ymin=value-se, ymax=value+se),
                size=.3, width=.2, 
                position=position_dodge(.9)) +
  geom_signif(annotations = c("**", "*"), y_position = c(1.15,1.25), 
              xmin = c(0.78, 1.78),xmax = c(1.23, 2.23), 
              tip_length = c(c(0.05, 0.8),c(0.05, 0.55)), vjust = 0) +
  scale_color_brewer("Set1") +
  xlab("RNAi Treated") +
  ylab("Relative Expression") +
  ggtitle("The Effect of RNAi on two genes")

Rplot08.png

参考资料：

1. R ggplot和ggsignif箱线图添加显著性差异标识
2. 神奇小工具丨ggplot绘图显著性添加工具---ggsignif