text: import random
  import scipy.stats as stat
  
  #cancerlist = ["ACC", "BLCA", "BRCA", "CESC", "CHOL", "COAD", "DLBC", "ESCA", "GBM", "HNSC", "KICH", "KIRC", "KIRP", "LGG", "LIHC", "LUAD", "LUSC", "MESO", "OV", "PAAD", "PCPG", "PRAD", "READ", "SARC", "SKCM", "STAD", "TGCT", "THCA", "THYM", "UCEC", "UCS", "UVM", "PANCANCER"]
  cancerlist = ["PANCANCER"]
  
  probe_count = 485577
  
  percentage = 0.05
  execution_number = 500
  
  sample_id = []
  cytoact = []
  
  ORDER = "RANDOM.05."
  
  def GetSample() :
      
      cytoact_file = open("TCGA_methylation_cowork_1.txt", 'r')
      header = cytoact_file.readline().split() # getting header
  
      id_posit = header.index("id") # sample ID positioning
      cytoact_posit = header.index("CytAct") # CytAct positioning
      cytodata = cytoact_file.readlines() # read data table
      cytoact_file.close()
  
      count = 0
  
      global sample_id
      global cytoact
      
      for line in cytodata :
          line = line.split()
          sample_id.append(line[id_posit].replace('_', '')) # sample ID extraction
          cytoact.append(float(line[cytoact_posit])) # CytAct extraction
  
          count += 1
      
      return count # Sample number return
      
  sample_number = GetSample()
  
  for i in range(0, len(cancerlist)) :
      
      input_tumor = open(cancerlist[i] + ".humanmethylation450.tumor.txt", 'r')
      
      sample_header1 = input_tumor.readline().split() # sample line
      del sample_header1[0]; del sample_header1[0]
      input_tumor.readline() # junk line
      
      length = len(sample_header1)
  
      for j in range(length) :
          sample_header1[j] = sample_header1[j][:15].replace('-', '')
  
      output_file = open(ORDER + cancerlist[i] + ".Correlation.Values." + str(execution_number) + ".Times.txt", 'w')
      
      sample_summation = []
      temp_summation = []
      
      for j in range(length) :
          if(sample_header1[j] not in sample_id) : temp_summation.append(-1)
          else : temp_summation.append(0)
          
      for iteration in range(execution_number) :
          sample_summation.append([])
          for j in range(length) :
              sample_summation[iteration].append(temp_summation[j])
      
      input_index = open(cancerlist[i] + ".Valid.Samples.For.Each.CpGsite.txt", 'r')
          
      for j in range(probe_count) :
            
          line = input_index.readline().split()
          site_id = line.pop(0)
  
          choosing_number = int(len(line) * percentage)
          
          line = map(int, line)
                  
          for iteration in range(execution_number) :
      
              chosen_index = random.sample(line, choosing_number)
              for index in chosen_index : sample_summation[iteration][index] += 1
  
      cor_cytoact = [] # valid cytact
      for j in range(length) :
          if(temp_summation[j] != -1) : cor_cytoact.append(cytoact[sample_id.index(sample_header1[j])])
          
      for iteration in range(execution_number) :
  
          cor_summation = []
          for j in range(length) :
              if(sample_summation[iteration][j] != -1) : cor_summation.append(sample_summation[iteration][j])
                  
          output_file.write(str(stat.spearmanr(cor_cytoact, cor_summation)[0]) + "\n")
  