R语言与生信系列①(R入门与临床三线表绘制)

代码分享：

#清除环境变量

rm(list=ls()) 



#加载所需的包

library("survival")

library("survminer")

library(dplyr)



#设置参数

options(stringsAsFactors = F)



#修改工作目录

setwd("C:\\Users\\czh\\Desktop\\material")



#读取数据

data <-  read.csv("dat.csv",header = T)



#删除缺失观测值

data <- na.omit(data)







#age单因素分析

data_age  <- data %>%

  dplyr::select(OS.Time, OS,age,ID)





res.cox <- coxph(Surv(OS.Time, OS) ~ age, data = data_age)

summary(res.cox)







#age数据提取

data_age  <- data_age %>%

  dplyr::select(age,ID)







#性别统计

tbl <- table(data$gender)

cbind(tbl,prop.table(tbl))







#gender数据提取

data_gender <- data

data_gender  <- data %>%

  dplyr::select(OS.Time, OS,gender,ID)





#gender单因素分析



data_gender <- subset(data_gender,gender =='FEMALE'| gender =='MALE')





data_gender$gender <- ifelse(data_gender$gender == 'FEMALE','1FEMALE','0MALE')



res.cox <- coxph(Surv(OS.Time, OS) ~ gender, data =data_gender)



summary(res.cox)







#grade数据提取

data_grade <- data

data_grade  <- data %>%

  dplyr::select(OS.Time, OS,grade,ID)





#grade单因素分析

data_grade  <- subset(data_grade ,grade=='High Grade'| grade=='Low Grade')

data_grade$grade <- ifelse(data_grade$grade == 'High Grade','1High','0low')

res.cox <- coxph(Surv(OS.Time, OS) ~ grade, data =data_grade )

summary(res.cox)







#tcell数据提取

data_tcell <- data

data_tcell  <- data %>%

  dplyr::select(OS.Time, OS,Tcell,ID)



#tcell单因素分析

data_tcell$Tcell <- ifelse(data_tcell$Tcell < median(data_tcell[,'Tcell']),'0low','1high ')





res.cox <- coxph(Surv(OS.Time, OS) ~Tcell, data = data_tcell)

summary(res.cox)







#tcell数据提取

data_tcell <- data

data_tcell  <- data %>%

  dplyr::select(Tcell,ID)





#stage数据提取

data_stage <- data

data_stage  <- data %>%

  dplyr::select(OS.Time, OS,stage,ID)



#stage单因素分析

data_stage <- subset(data_stage, stage=='Stage II'|stage=='Stage III'| stage=='Stage IV')



res.cox <- coxph(Surv(OS.Time, OS) ~ stage, data =data_stage)

summary(res.cox)





#多因素分析数据准备

data_new <- merge(data_age,data_stage,by='ID')  

data_new <- merge(data_new,data_tcell,by='ID')  





#多因素分析

res.cox <- coxph(Surv(OS.Time, OS) ~ age + stage  + Tcell , 

                 data = data_new  )

summary(res.cox)