R语言循环绘制柱状图

用户1359560

发布于 2020-12-01 10:37:22

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代码可运行

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代码可运行

循环绘制正常与肿瘤两组的柱状图

第一步：合并数据及

# ===================================================
#   
#   
#   
# ===================================================

rm(list=ls()) 

setwd('D:\\SCIwork\\F24\\OSCC\\DEG')

data <- read.csv('mRNA_exprSet.csv', header = T, row.names = 1)

data[1:4,1:4]

gene <- c('BUB1', 'BUB2', 'BUB3', 'BUB4')

dt <- data[which(rownames(data) %in% gene),]

dt <- as.data.frame(t( dt))

dt <- log2(dt +1)

# ===================================================


metadata <- data.frame(rownames(dt))


for (i in 1:length(metadata[,1])) {
  num <- as.numeric(as.character(substring(metadata[i,1],14,15)))
  if (num == 1 ) {metadata[i,2] <- "Tumor"}
  if (num != 1) {metadata[i,2] <- "Normal"}
}
names(metadata) <- c("id","group")
metadata$group <- as.factor(metadata$group)

table(metadata$group )

dt$id <- rownames(dt)

dt <- merge( metadata, dt, by='id')

第二步：循环绘图

# ===================================================


setwd('D:\\SCIwork\\F24\\OSCC\\grade\\TN')

pal <- c('#00A0D2', '#B24646')


for (i in 3:ncol(dt)) {
  
  
  gene <-  as.character(colnames(dt)[i])

  p <- ggboxplot(dt, x="group",
                 y = gene, color = "group",
                 palette = pal, add = "jitter")
  # 添加p值
  p <- p + stat_compare_means()
  ggsave(filename = paste( gene, '.pdf', sep = ''),
         width = 8, height = 8, units = "cm")}

循环不同grade的柱状图

# ===================================================
#   
#   
#   
# ===================================================


library(dplyr)

library(tidyr)

library(tidyverse)


rm(list=ls()) 

setwd('D:\\SCIwork\\F24\\OSCC\\DEG')

data <- read.csv('tumor_exp.csv', header = T, row.names = 1)

data[1:4,1:4]

gene <- c('BUB1', 'BUB2', 'BUB3', 'BUB4')
dt <- data[which(rownames(data) %in% gene),]

dt <- as.data.frame(t( dt))

dt <- log2(dt +1)

dt$Barcode <- substr(x=rownames(dt), 
                       start = 1, stop = 12)

dt$Barcode <- chartr(old='.', new = '-', x=dt$Barcode)

# ===================================================

sur  <- read.csv('survival_OSCC.csv', header = T, row.names = 1)

sur <- sur %>% 
  select( 'Barcode',  "Grade")

dt <- merge(sur, dt, by='Barcode')

dt$Grade <- as.factor(as.character(dt$Grade))


setwd('D:\\SCIwork\\F24\\OSCC\\grade\\grade')

pal <- c('#191970','#87CEFA','#FFA07A', '#B22222')


for (i in 3:ncol(dt)) {
  
  
  gene <-  as.character(colnames(dt)[i])
  
  p <- ggboxplot(dt, x="Grade",
                 y = gene, color = "Grade",
                 palette = pal, add = "jitter")
  # 添加p值
  p <- p + stat_compare_means()
  ggsave(filename = paste( gene, '.pdf', sep = ''),
         width = 8, height = 8, units = "cm")}