如何將柱狀圖和箱線圖畫一起

請(qǐng)大家查看原文
參考推文:http://www.itdecent.cn/p/308874fa1e6f
接下來我們就一步一步來畫:
我們知道用R畫圖最重要的兩點(diǎn):1.數(shù)據(jù)類型;2.數(shù)據(jù)結(jié)構(gòu)

數(shù)據(jù)預(yù)處理

首先,我們先來讀取數(shù)據(jù)

file1 = read.table('file1')
file2 = read.table('file2')

file1

file2

再來就是處理數(shù)據(jù):

#對(duì)file1按A,B的標(biāo)簽的組分離
c1 = which(file1$V3 == 'A')
c2 = which(file1$V3 == 'B')
file1_c1 = file1[c1,]
file1_c2 = file1[c2,]

按A,B分離

file1_c1

file1_c2

顯著性檢驗(yàn)

注意下下file1,file2是不同來源,分A,B組對(duì)其做t.text

#對(duì)file1,file2 分A,B組做t.test
t1 = t.test(rep(df2$V4[2],length(df1_g1$V4)), df1_g1$V4)$p.value
t2 = t.test(df1_g2$V4,rep(df2$V4[1],length(df1_g2$V4)))$p.value

做柱形圖的表

這里要加a來區(qū)分,稍后我們解密

bar = data.frame(
  x = c(as.character(file2$V3[2]),as.character(file2$V3[1])),
  y = c(file2$V4[2],file2$V4[1])
)
#先分A,B兩類,圖1
bar$x = c("B",'A')
#在加上a作為區(qū)分,圖2
bar$x = c("Ba",'Aa')

圖1

圖2

做箱線圖的表

box = rbind(file1_c1,file1_c2)
box = box[,-c(1,2)]
box = as.data.frame(box)
colnames(box) = c('x','y')
#先分A,B兩類,圖3
box$x = c(rep("B",5),rep('A',5))
#在加上c作為區(qū)分,圖4
box$x = c(rep("Bc",5),rep('Ac',5))

圖3

圖4

畫圖

ggplot()+
  geom_bar(data = daf[1:2,],aes(x = x,y = y,fill = type),stat = 'identity',width = 0.9,alpha= 0.8)+
  geom_bar(data = daf[13:14,],aes(x = x,y = y),stat = 'identity',width = 0.2)+
  geom_boxplot(data = daf[3:12,],aes(x = x, y =y,fill = type),width = 0.9,alpha = 0.8)

image.png

我們看這幅圖的橫坐標(biāo)的映射,不難發(fā)現(xiàn)a標(biāo)簽是來自于file1 的數(shù)據(jù),c標(biāo)簽是來自于file2;A,B則是分的類

美化這個(gè)圖

#重新做表,圖5
bar_label= data.frame(
  x = c('Bb','Ab'),
  y = c(NA,NA)
)

daf = rbind(bar,box,bar_label)
daf$type = c('B','A',rep('B',5),rep('A',5),'B','A')

library(ggsci)

ggplot()+
  geom_bar(data = daf[1:2,],aes(x = x,y = y,fill = type),stat = 'identity',width = 0.9,alpha= 0.8)+
  geom_bar(data = daf[13:14,],aes(x = x,y = y),stat = 'identity',width = 0.2)+
  geom_boxplot(data = daf[3:12,],aes(x = x, y =y,fill = type),width = 0.9,alpha = 0.8)+
  scale_x_discrete(labels = c('','B','','','A',''))+ #修改x坐標(biāo)軸內(nèi)容
  scale_fill_lancet()+ #修改顏色
  theme_bw()+
  theme(
    axis.text =  element_text(face = 'bold',color = 'black',size = 12),
    axis.title =  element_text(face = 'bold',color = 'black',size = 14, hjust = .5),
    legend.text = element_text(face = 'bold',color = 'black',size = 12),
    legend.title = element_blank(),
    legend.position = 'bottom',
    legend.direction = 'horizontal'
  )+
  xlab('Sample Name')+
  ylab('Value')

圖5

引入兩個(gè)NA是為了在x軸上占個(gè)空位,即用Ab和Bb在X軸上占位:

占空位

最后效果如圖:

image.png

加上顯著性標(biāo)簽

#先做t.test
t1 = t.test(rep(file2$V4[2],length(file1_c1$V4)), file1_c1$V4)$p.value
t2 = t.test(file1_c2$V4,rep(file2$V4[1],length(file1_c2$V4)))$p.value
#做成data.frame,圖6
label_daf = data.frame(
  x = c('Bb','Ab'),
  y = c(13.5,13.5),
  label = paste0('p.value = ',                 c(as.character(round(t1,3)),as.character(round(t2,3))))
)

#做網(wǎng)格線,圖7
seg_daf = data.frame(
  x = c('Ba','Aa','Ba','Bc','Aa','Ac'),
  xmax = c('Bc','Ac','Ba','Bc','Aa','Ac'),
  y = c(13,13,12.5,12.5,12.5,12.5),
  ymax = c(13,13,13,13,13,13)
)

圖6

file1和file2之間的顯著性,這個(gè)y是在圖上顯示的坐標(biāo)

圖7

見下圖:
x指的是網(wǎng)格線的豎線部分,也就是說x只映射于Aa,Ac,Ba和Bc這四個(gè)位置;y值橫線部分,數(shù)值是在圖上的位置

image.png

美化圖

ggplot()+
  geom_bar(data = daf[1:2,],aes(x = x,y = y,fill = type),stat = 'identity',width = 0.9,alpha= 0.8)+
  geom_bar(data = daf[13:14,],aes(x = x,y = y),stat = 'identity',width = 0.2)+
  geom_boxplot(data = daf[3:12,],aes(x = x, y =y,fill = type),width = 0.9,alpha = 0.8)+
  geom_segment(data = seg_daf,aes(x = x,y = y,xend = xmax,yend = ymax),color = 'black',size = 0.2)+
  geom_text(data = label_daf,aes(x = x,y = y,label = label),fontface = 'bold',color = 'black',size = 5)+
  scale_x_discrete(labels = c('','B','','','A',''))+
  scale_fill_lancet()+
  theme_bw()+
  theme(
    axis.text =  element_text(face = 'bold',color = 'black',size = 12),
    axis.title =  element_text(face = 'bold',color = 'black',size = 14, hjust = .5),
    legend.text = element_text(face = 'bold',color = 'black',size = 12),
    legend.title = element_blank(),
    legend.position = 'bottom',
    legend.direction = 'horizontal'
  )+
  xlab('Sample Name')+
  ylab('Value')

最終效果圖見下圖:

image.png