ROC

 # -*- coding: utf-8 -*-
 # __author__ = "JieYao"

 from biocluster.agent import Agent
 from biocluster.tool import Tool
 import os
 import string
 import types
 import subprocess
 from biocluster.core.exceptions import OptionError

 class RocAgent(Agent):
     """
     需要calc_roc.pl
     version v1.1
     author: JieYao
     last_modifued:2016.08.22
     """

     def __init__(self, parent):
         super(RocAgent, self).__init__(parent)
         options = [
             {"name": "mode", "type": "int", "default":1},
             {"name": "genus_table", "type": "string"},
             {"name": "group_table", "type": "string"},
             {"name": "method", "type": "string", "default":""},
             {"name": "name_table", "type": "string", "default":""},
             {"name": "top_n", "type": "int", "default": 20}
             ]
         self.add_option(options)
         self.step.add_steps('RocAnalysis')
         self.on('start', self.step_start)
         self.on('end', self.step_end)

     def step_start(self):
         self.step.RocAnalysis.start()
         self.step.update()

     def step_end(self):
         self.step.RocAnalysis.finish()
         self.step.update()

     def check_options(self):
         if not os.path.exists(self.option('genus_table')):
             raise OptionError("必须提供Genus Table")
         if not os.path.exists(self.option('group_table')):
             raise OptionError("必须提供分组表格")
         if self.option('method'):
             if self.option('method') not in ['sum', 'average', 'median']:
                 raise OptionError("丰度计算方法只能选择sum,average,median之一")
         if self.option('mode') == 2:
             if not os.path.exists(self.option('name_table')):
                 raise OptionError("Mode 2 模式下必须提供物种名列表文件")
         os.system('cat %s | awk -F "\t" \'{ print $1 }\' > tmp.txt' %(self.option('genus_table')))
         genus_data = open("tmp.txt", "r").readlines()[1:]
         os.remove('tmp.txt')
         genus_data = map(string.rstrip, genus_data)
         sample_data = open(self.option('genus_table'), "r").readline().strip().split()[1:]

         group_data = open(self.option('group_table'), "r").readlines()[1:]
         group_data = map(string.strip, group_data)
         for s in group_data:
             if s.split()[0] not in sample_data:
                 raise OptionError("物种%s不在Genus Table中" % s.split()[0])
             if s.split()[1] not in ['','']:
                 raise OptionError("物种分组只能有0和1！")

         if self.option('mode')==2:
             name_data = open(self.option('name_table'), "r").readlines()[1:]
             name_data = map(string.strip, name_data)
             for s in name_data:
                 if s not in genus_data:
                     raise OptionError("物种%s不在Genus Table中" % s)

         if self.option('mode')==1:
             if self.option('top_n')>len(genus_data):
                 raise OptionError("选择丰度前N高物种时，设定的N多于物种总数：%d>%d" %(self.option('top_n'), len(genus_data)))

         return True

     def set_resource(self):
         """
         """
         self._cpu = 2
         self._memory = ''

     def end(self):
         result_dir = self.add_upload_dir(self.output_dir)
         result_dir.add_relpath_rules([
                 [".", "", "ROC分析结果目录"],
                 ["./roc_curve.pdf", "pdf", "ROC受试者工作特征曲线图"],
                 ["./roc_auc.xls", "xls", "ROC受试者工作特征曲线-AUC VALUE"]
                 ])
         print self.get_upload_files()
         super(RocAgent, self).end()

 class RocTool(Tool):
     def __init__(self, config):
         super(RocTool, self).__init__(config)
         self._version = '1.0.1'

     def run(self):
         """
         运行
         """
         super(RocTool, self).run()
         self.run_roc_perl()

     def run_roc_perl(self):
         """
         运行calc_roc.perl
         """
         os.system('export PATH=/mnt/ilustre/users/sanger-dev/app/gcc/5.1.0/bin:$PATH')
         os.system('export LD_LIBRARY_PATH=/mnt/ilustre/users/sanger-dev/app/gcc/5.1.0/lib64:$LD_LIBRARY_PATH')
         cmd = self.config.SOFTWARE_DIR + '/program/perl/perls/perl-5.24.0/bin/perl ' + self.config.SOFTWARE_DIR + '/bioinfo/meta/scripts/plot_roc.pl '
         cmd += '-o %s ' %(self.work_dir + '/ROC/')
         cmd += '-i %s ' %(self.option('genus_table'))
         cmd += '-mode %d ' %(self.option('mode'))
         cmd += '-group %s ' %(self.option('group_table'))
         if self.option('mode')==2:
             cmd += '-name %s ' %(self.option('name_table'))
         if self.option('method'):
             cmd += '-method %s ' %(self.option('method'))
         if self.option('mode')==1:
             cmd += '-n %d ' %(self.option('top_n'))
         cmd += '-labels F '
         self.logger.info('开始运行calc_roc.pl计算ROC相关数据')

         try:
             subprocess.check_output(cmd, shell=True)
             self.logger.info('生成 roc.cmd.r 成功')
         except subprocess.CalledProcessError:
             self.logger.info('生成 roc.cmd.r 失败')
             self.set_error('无法生成 roc.cmd.r 文件')
         try:
             subprocess.check_output(self.config.SOFTWARE_DIR +
                                     '/program/R-3.3.1/bin/R --restore --no-save < %s/roc.cmd.r' % (self.work_dir + '/ROC'), shell=True)
             self.logger.info('ROC计算成功')
         except subprocess.CalledProcessError:
             self.logger.info('ROC计算失败')
             self.set_error('R运行计算ROC失败')
             raise "运行R脚本计算ROC相关数据失败"
         self.logger.info('运行calc_roc.pl程序进行ROC计算完成')
         allfiles = self.get_roc_filesname()
         self.linkfile(self.work_dir + '/ROC/' + allfiles[0], 'roc_curve.pdf')
         self.linkfile(self.work_dir + '/ROC/' + allfiles[1], 'roc_auc.xls')
         self.end()

     def linkfile(self, oldfile, newname):
         newpath = os.path.join(self.output_dir, newname)
         if os.path.exists(newpath):
             os.remove(newpath)
         os.link(oldfile, newpath)

     def get_roc_filesname(self):
         filelist = os.listdir(self.work_dir + '/ROC')
         roc_curve = None
         roc_auc = None
         for name in filelist:
             if 'roc_curve.pdf' in name:
                 roc_curve = name
             elif 'roc_aucvalue.xls' in name:
                 roc_auc = name
         if (roc_curve and roc_auc):
             return [roc_curve, roc_auc]
         else:
             self.set_error("未知原因，ROC计算结果丢失")
     

  #!/usr/bin/perl

 use strict;
 use warnings;
 use Getopt::Long;
 my %opts;
 my $VERSION = "v1.20160817"; 

 GetOptions( \%opts,"mode=s","i=s","group=s","o=s","n=s","method=s","name=s","ncuts=i","labels=s","labelsize=s","rocci=s","siglevel=f","w=f","h=f","facet_wrap=s","theme=s");
 my $usage = <<"USAGE";
        Program : $
        Discription:
        Version : $VERSION
        Usage :perl $ [options]
                         -mode    * or  or ; The Receiver:)The relative abundance of the top n  Bacteria(could analysis with more than one group)
                                                            )The relative abundance of special bacteria(one or more)
                                                            )The receiver is any other factors
             -i    *Input genus table file(or other Taxonomic level) or any other factors(mode_3).
             -group  *Group name in mapping file .
                         -o    *Output dir
                         -n    (*mode_1)Top n genus or other taxonomic level(relative abundance)
                         -method (*mode_1)If you choose the mode_2 to analyze, you can also choose the analysis "methed". If you don't have a choice, you will make a separate analysis of them.   Follow method are available:sum, average, median
                         -name    (*mode_2)the name of Bacteria
             -ncuts    Number of cutpoints to display along each curve.Default:20
             -labels    Logical, display cutoff text labels:Default:F
             -labelsize    Size of cutoff text labels.Default:3
             -rocci    Confidence regions for the ROC curve.Default:F
             -siglevel    Significance level for the confidence regions.Default:0.05
             -w    default:6
             -h    default:5
             -facet_wrap      Logical,display group in different panel.Default:F
             -theme  themes for display roc.Follow themes are available:theme_bw,theme_classic,theme_dark,theme_gray,theme_light.Default:theme_bw
        Example:$0 -mode 1 -i genus.xls -group group.txt -o output_dir -n 30  -labels F -method sum
                    $0 -mode 2 -i genus.xls -group group_1.txt -o output_dir -name name.txt  -labels F -w 7.8
                    $0 -mode 2 -i genus.xls -group group_1.txt -o output_dir -name name.txt  -labels F -method sum
                    $0 -mode 3 -i factor.txt -group group.txt -o output_dir -labels F -w 7.8

 USAGE

 die $usage if(!($opts{mode}&&$opts{i}&&$opts{group}&&$opts{o}));
 #die $usage if(!(($opts{mode}==F)&&$opts{i}&&$opts{group}&&$opts{o}&&$opts{name}));

 $opts{n}=defined $opts{n}?$opts{n}:"20";
 $opts{method}=defined $opts{method}?$opts{method}:"chengchen.ye";
 $opts{name}=defined $opts{name}?$opts{name}:"NULL";
 $opts{ncuts}=defined $opts{ncuts}?$opts{ncuts}:20;
 $opts{labels}=defined $opts{labels}?$opts{labels}:"F";
 $opts{labelsize}=defined $opts{labelsize}?$opts{labelsize}:"3";
 $opts{w}=defined $opts{w}?$opts{w}:6;
 $opts{h}=defined $opts{h}?$opts{h}:5;
 $opts{facet_wrap}=defined $opts{facet_wrap}?$opts{facet_wrap}:"F";
 $opts{theme}=defined $opts{theme}?$opts{theme}:"";
 $opts{rocci}=defined $opts{rocci}?$opts{rocci}:"F";
 $opts{siglevel}=defined $opts{siglevel}?$opts{siglevel}:"0.05";

 if(! -e $opts{o}){
         `mkdir $opts{o}`;
 }

 open CMD,">$opts{o}/roc.cmd.r";

 print CMD "
     library(plotROC)

         group <- read.table(\"$opts{group}\",header=T,check.names=F,comment.char=\"\")
         otu_table <-read.table(\"$opts{i}\",sep=\"\t\",head=T,check.names = F,row.names=1)
         y<-length(otu_table[1,])

 ###The Receiver:A)The relative abundance of the Bacteria
 if($opts{mode}==1){
         group<-as.data.frame(group)
         x<-length(group[1,])
         ###D
         D<-group[,2]

         ####M
         otu_table<-cbind(otu_table,rowsum=rowSums(otu_table))
         otu_table<- otu_table[order(otu_table[,y+1],decreasing=T),]
         otu_table_top20<- otu_table[1:$opts{n},]
              ####sum
 if(\"$opts{method}\"==\"sum\" ){
              v<-y+1
              m<-data.frame(colSums(otu_table_top20))[-v,]
 }

              ####average
 if(\"$opts{method}\"==\"average\"){
              v<-y+1
              m<-data.frame(colSums(otu_table_top20)/$opts{n})[-v,]
 }

              ####median
 if(\"$opts{method}\"==\"median\"){
              top20<-otu_table_top20[,1:y]
              m<-as.matrix(as.matrix(top20[ceiling($opts{n}/2),])[1,])
 }        

          ###Z
          Z<-c(rep(\"group1\",y))
          i<-2

          while (i <= x-1) {
               ###D
               D<-c(D,group[,i+1])
               ###M
               m<-c(m,m)
               ###Z
               w<-paste(\"group\",i,sep=\"\")
               Z<-c(Z,rep(w,y))
               i <- i +1
          }
          #
          M <- scale(m, center=T,scale=T)  #标准化
          if(x!=2){
              rocdata<- data.frame(diagnosis = D, measure = M, group = Z)
              p <- ggplot(rocdata, aes(m = measure , d = diagnosis ,color=group)) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

              if($opts{rocci}==T){
                  p <- p + geom_rocci(sig.level=$opts{siglevel})
              }

              if($opts{facet_wrap}==T){
                  p <- p + facet_wrap(~ group) + theme(axis.text = element_text(size = 4))
              }

          }

          if(x==2){

              rocdata<- data.frame(diagnosis = D, measure = M)
              p <- ggplot(rocdata, aes(m = measure , d = diagnosis )) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

          if($opts{rocci}==T){
              p <- p + geom_rocci(sig.level=$opts{siglevel})
          }

         }
 x<-x-1
 }

 ###The Receiver:2)The relative abundance of special bacteria.
 if($opts{mode}==2){

 if(\"$opts{method}\"==\"chengchen.ye\"){
        name <- read.table(\"$opts{name}\",header=T,check.names=F,comment.char=\"\")
        name<-as.data.frame(name)
        x<-length(name[,1])
        a<-as.character(name[1,1])
        D<-group[,2]
        m<-as.matrix(as.matrix(otu_table)[a,])

        Z<-c(rep(a,y))
        i<-2
        while (i <= x) {
            D<-c(D,group[,2])
            a<-as.character(name[i,1])
            m<-c(m,as.matrix(as.matrix(otu_table)[a,]))
            a<-as.character(name[i,1])
            Z<-c(Z,rep(a,y))
            i <- i +1
        }

         M <- scale(m, center=T,scale=T)  #标准化
 if(x!=1){
         rocdata<- data.frame(diagnosis = D, measure = M, Bacteria = Z)
     p <- ggplot(rocdata, aes(m = measure , d = diagnosis ,color=Bacteria)) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

 if($opts{rocci}==T){
     p <- p + geom_rocci(sig.level=$opts{siglevel})
 }

 if($opts{facet_wrap}==T){
     p <- p + facet_wrap(~ group) + theme(axis.text = element_text(size = 4))
     }

 }

 if(x==1){

         rocdata<- data.frame(diagnosis = D, measure = M)
         p <- ggplot(rocdata, aes(m = measure , d = diagnosis )) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

 if($opts{rocci}==T){
         p <- p + geom_rocci(sig.level=$opts{siglevel})
         }
 }
 }
 ######choose method
 if(\"$opts{method}\"!=\"chengchen.ye\"){
 name <- read.table(\"name.txt\",header=T,check.names=F,comment.char=\"\")
 otu_table<-as.data.frame(otu_table)
 nu<-length(name[,1])

 genus<-otu_table[as.character(name[1,1]),]
 i<-2
 while (i <= nu) {
 genus<-rbind(genus,otu_table[as.character(name[i,1]),])
 i<-i+1
 }
 genus
 group<-as.data.frame(group)
 x<-length(group[1,])
     ###D
         D<-group[,2]

     ####M
         genus<-cbind(genus,rowsum=rowSums(genus))
         genus<- genus[order(genus[,y+1],decreasing=T),]        

              ####sum
 if(\"$opts{method}\"==\"sum\" ){
              hh<-y+1
              m<-data.frame(colSums(genus))[-hh,]
 }

              ####average
 if(\"$opts{method}\"==\"average\"){
              hh<-y+1
              m<-data.frame(colSums(genus)/nu)[-hh,]
 }

              ####median
 if(\"$opts{method}\"==\"median\"){
              genus_order<-genus[,1:y]
              m<-as.matrix(as.matrix(genus_order[ceiling(nu/2),])[1,])
 }
      ###Z
          Z<-c(rep(\"group1\",y))
          i<-2

          while (i <= x-1) {
               ###D
               D<-c(D,group[,i+1])
               ###M
               m<-c(m,m)
               ###Z
               w<-paste(\"group\",i,sep=\"\")
               Z<-c(Z,rep(w,y))
               i <- i +1
          }
          #
          M <- scale(m, center=T,scale=T)  #标准化
          if(x!=2){
              rocdata<- data.frame(diagnosis = D, measure = M, group = Z)
              p <- ggplot(rocdata, aes(m = measure , d = diagnosis ,color=group)) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

              if($opts{rocci}==T){
                  p <- p + geom_rocci(sig.level=$opts{siglevel})
              }

              if($opts{facet_wrap}==T){
                  p <- p + facet_wrap(~ group) + theme(axis.text = element_text(size = 4))
              }

          }

          if(x==2){

              rocdata<- data.frame(diagnosis = D, measure = M)
              p <- ggplot(rocdata, aes(m = measure , d = diagnosis )) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

          if($opts{rocci}==T){
              p <- p + geom_rocci(sig.level=$opts{siglevel})
          }

         }

 x<-x-1

 }
 }

 ###The Receiver:3)The receiver is any other factors
 if($opts{mode}==3){

 factor <-read.table(\"$opts{i}\",sep=\"\t\",head=T,check.names = F,row.names=1)
 x<-length(factor[1,])

 D<-group[,2] 

 m<-factor[,1]
 ####Z
 factor_name <-read.table(\"$opts{i}\",sep=\"\t\",check.names = F,row.names=1)
 name<-as.character(factor_name[1,1])
 len<-length(factor[,1])
 Z<-c(rep(name,len))
 i<-2
 while (i <= x) {
     D<-c(D,D)
         m<-c(m,factor[,i])
             name<-as.character(factor_name[1,i])
                 Z<-c(Z,rep(name,len))
                     i <- i +1
                     }
 M <- scale(m, center=T,scale=T)

 if(x!=1){
         rocdata<- data.frame(diagnosis = D, measure = M, factor = Z)
         p <- ggplot(rocdata, aes(m = measure , d = diagnosis ,color=factor)) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

 if($opts{rocci}==T){
         p <- p + geom_rocci(sig.level=$opts{siglevel})
 }

 if($opts{facet_wrap}==T){
         p <- p + facet_wrap(~ group) + theme(axis.text = element_text(size = 4))
         }

 }

 if(x==1){

         rocdata<- data.frame(diagnosis = D, measure = M)
         p <- ggplot(rocdata, aes(m = measure , d = diagnosis )) + geom_roc(labels=$opts{labels},labelsize=$opts{labelsize},n.cuts=$opts{ncuts}) + style_roc(major.breaks = c(0, 0.25, 0.5, 0.75, 1), theme=$opts{theme},xlab=\"1-Specificity\",ylab=\"Sensitivity\") 

 if($opts{rocci}==T){
         p <- p + geom_rocci(sig.level=$opts{siglevel})
         }

 }

 }

 ### Caculate the Area under the ROC curve
 p.auc <- calc_auc(p)
 write.table(p.auc,\"$opts{o}/roc_aucvalue.xls\",col.names=T,row.names=F,sep=\"\t\",quote=F)

 if($opts{mode}==1){

 ###paste AUC to graph
 if(x==1){

 test_auc<-paste(\"AUC=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")

 p<-p + geom_text(x=0.8,y=0.1,label=test_auc,size=4)

 }

 if(x==2){
 test_auc1<-paste(\"AUC_group1=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC_group2=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=0.8,y=0.21,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.15,label=test_auc2,size=4,colour=\"black\")

 }

 if(x==3){
 test_auc1<-paste(\"AUC_group1=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC_group2=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 test_auc3<-paste(\"AUC_group3=\",round(p.auc[3,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=0.8,y=0.18,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.12,label=test_auc2,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.06,label=test_auc3,size=4,colour=\"black\")
 }

 }

 if($opts{mode}==2){

 if(\"$opts{method}\"==\"chengchen.ye\"){

 ###auc_name
 auc_name<-as.data.frame(sort(name[,1],decreasing=F))

 ###paste AUC to graph
 if(x==1){

 test_auc<-paste(\"AUC=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")

 p<-p + geom_text(x=0.8,y=0.1,label=test_auc,size=4)

 }

 if(x==2){
 test_auc1<-paste(\"AUC\(\",as.character(auc_name[1,1]),\"\)=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC\(\",as.character(auc_name[2,1]),\"\)=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=Inf,y=-Inf,hjust=1.2,vjust=-4,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=Inf,y=-Inf,hjust=1.2,vjust=-2,label=test_auc2,size=4,colour=\"black\")

 }

 if(x==3){
 test_auc1<-paste(\"AUC\(\",as.character(auc_name[1,1]),\"\)=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC\(\",as.character(auc_name[2,1]),\"\)=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 test_auc3<-paste(\"AUC\(\",as.character(auc_name[3,1]),\"\)=\",round(p.auc[3,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=Inf,y=-Inf,hjust=1.1,vjust=-6,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=Inf,y=-Inf,hjust=1.1,vjust=-4,label=test_auc2,size=4,colour=\"black\")
 p<-p + geom_text(x=Inf,y=-Inf,hjust=1.1,vjust=-2,label=test_auc3,size=4,colour=\"black\")
 }

 }

 if(\"$opts{method}\"!=\"chengchen.ye\"){

 ###paste AUC to graph
 if(x==1){

 test_auc<-paste(\"AUC=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")

 p<-p + geom_text(x=0.8,y=0.1,label=test_auc,size=4)

 }

 if(x==2){
 test_auc1<-paste(\"AUC_group1=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC_group2=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=0.8,y=0.3,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.25,label=test_auc2,size=4,colour=\"black\")

 }

 if(x==3){
 test_auc1<-paste(\"AUC_group1=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC_group2=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 test_auc3<-paste(\"AUC_group3=\",round(p.auc[3,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=0.8,y=0.22,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.16,label=test_auc2,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.1,label=test_auc3,size=4,colour=\"black\")
 }
 }
 }

 if($opts{mode}==3){

 ###auc_name

 auc_name<-as.data.frame(sort(factor_name[1,],decreasing=F))

 ###paste AUC to graph
 if(x==1){

 test_auc<-paste(\"AUC=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")

 p<-p + geom_text(x=0.8,y=0.1,label=test_auc,size=4)

 }

 if(x==2){
 test_auc1<-paste(\"AUC_\",as.character(auc_name[1,1]),\"=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC_\",as.character(auc_name[1,2]),\"=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=Inf,y=-Inf,hjust=1.2,vjust=-4,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=Inf,y=-Inf,hjust=1.2,vjust=-2,label=test_auc2,size=4,colour=\"black\")

 }

 if(x==3){
 test_auc1<-paste(\"AUC_\",as.character(auc_name[1,1]),\"=\",round(p.auc[1,3] * 100, 2),\"%\",sep = \"\")
 test_auc2<-paste(\"AUC_\",as.character(auc_name[1,2]),\"=\",round(p.auc[2,3] * 100, 2),\"%\",sep = \"\")
 test_auc3<-paste(\"AUC_\",as.character(auc_name[1,3]),\"=\",round(p.auc[3,3] * 100, 2),\"%\",sep = \"\")
 p<-p + geom_text(x=0.8,y=0.18,label=test_auc1,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.12,label=test_auc2,size=4,colour=\"black\")
 p<-p + geom_text(x=0.8,y=0.06,label=test_auc3,size=4,colour=\"black\")
 }

 }

 pdf(\"$opts{o}/roc_curve.pdf\",width=$opts{w},height=$opts{h})
 p
 dev.off()

 ";

 `R --restore --no-save < $opts{o}/roc.cmd.r`;