1. for(a in names(PFS_Rizi_AD_gene1[,5:ncol(PFS_Rizi_AD_gene1)]))
  2. {
  3.   i=gene1[,a]
  4.   while (TRUE %in% i) 
  5.   {
  6.     fit<-survfit(Surv(PFS_MONTHS,PFS_STATUS)~PFS_Rizi_AD_gene1[,i],PFS_Rizi_AD_gene1)
  7.     p <- ggsurvplot(fit, risk.table = T, pval = T, pval.method = TRUE,
  8.                     palette = surv_color,
  9.                     xlab = "Time (Months)",
  10.                     surv.median.line = "hv",
  11.                     ylab = "PFS(%)",
  12.                     legend.labs = c("WILD", "MUT"))
  13.     tiff(paste("results_AD/gene_", i,"_surv", ".tiff"), compression="lzw",units="in",res=600,pointsize=8,width=6, height=7)
  14.     print(p,newpage = FALSE)
  16.     break
  17.   }
  18.   while (!is.null(dev.list()))  
  19.     dev.off()
  20. }

Demo

  1. gene1=read.table("C:\\Users\\Stanley\\Desktop\\PFS_AD_gene1.csv",sep=",",header=TRUE)
  3. for(a in names(gene1[,6:ncol(gene1)]))
  4. {
  5.   i=gene1[,a]
  7.  while (TRUE %in% i) 
  8.    {
  9.    print(a)
  10.    plot(c(1:6),c(1:6),main="test",type="b",xlim = c(0,7),ylim = c(0,7))
  12.    break
  13.    }
  15.   while (!is.null(dev.list()))  ## 
  16.     dev.off()
  17. }