for循环批量生存分析出图

for循环批量生存分析出图
尝试一下怎么批量生成图片，不过有点小bug还未解决。

library(survival)
library(survminer)

head(ALL)   #我的数据
#OS     OS_Status   gene1   gene2   gene3   gene4   gene5   gene6   gene7   gene8   gene9  gene10
# 49.97         0    Gain    Gain Diploid Diploid    Gain    Loss    Loss    Loss    Gain Diploid
# 36.27         0 Diploid Diploid Diploid Diploid Diploid Diploid Diploid Diploid Diploid Diploid
# 19.68         1    Loss Diploid    Gain    Gain    Loss    Loss    Loss    Loss Diploid Diploid
# 31.50         0 Diploid Diploid Diploid Diploid    Loss Diploid Diploid    Loss    Loss Diploid
# 53.45         1 Diploid Diploid Diploid Diploid    Gain Diploid Diploid Diploid    Loss Diploid
# 68.50         0 Diploid Diploid Diploid Diploid Diploid    Loss Diploid Diploid    Loss    Gain

survfit估计生存率

for (i in 3:12){
  surv=as.formula(paste('Surv(OS, OS_Status==1) ~ ',colnames(ALL)[i]))
  KM <- survfit(surv,
                data = ALL, 
                type = 'kaplan-meier', 
                conf.type = 'log')

#两两比较生存率是否有差异
  p=pairwise_survdiff(surv, data = ALL,rho = 0)
     
#输出p<0.05的值
  a=p$p.value
  if (is.na(a[1])){
    a[1]=10
  } #这里是将NA值去掉
  else if(is.na(a[2])){
    a[2]=10
  }
  else if (a[1]<0.05 | a[2]<0.05){
    print(paste(colnames(ALL)[i],p$p.value,sep = ' '))
  }    
}

用survminer包画生存曲线

#将每个基因提取出来作为一个List
D=list()
for (i in 3:12){
  j=i-2
  D[[j]]=data.frame('OS'=ALL$OS,
                    'OS_Status'=ALL$OS_Status,
                    'Type'=ALL[,i])
}

#绘图
for (i in 1:length(D)){
  x=D[[i]]
  KM_survfit <- survfit(Surv(OS, OS_Status==1) ~ Type
                        data = x，
                        type = 'kaplan-meier', 
                        conf.type = 'log')
                        )
  j=i+2 #这个2是因为我数据里从第三列开始才是基因
  ggsave(filename = paste0(colnames(ALL)[j-1],'_OS','.pdf'),width = 5,height = 5) #就是这个bug，colnames我要设置成j-1而不是j最后输出结果才正确       
  p=ggsurvplot(KM_survfit,
               data = x,
               pval = T,  #还有就是pairwise的p值好像不能自动生成
               title=paste('Overall Survival -',colnames(ALL)[j],sep = ' ')) #这里colnames为j又没有问题
  print(p)
  dev.off()
 }

最终结果

Rplot01.jpeg