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1 #!/usr/bin/env python
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2 """
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3 usage: %prog bed_file_1 bed_file_2 out_file
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4 -1, --cols1=N,N,N,N: Columns for chr, start, end, strand in first file
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5 -2, --cols2=N,N,N,N,N: Columns for chr, start, end, strand, name/value in second file
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6 """
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7
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8 import collections
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9 import sys
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10 #import numpy
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11 from galaxy import eggs
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12 import pkg_resources
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13 pkg_resources.require( "bx-python" )
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14 from galaxy.tools.util.galaxyops import *
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15 from bx.cookbook import doc_optparse
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16
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17
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18 #export PYTHONPATH=~/galaxy/lib/
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19 #running command python WeightedAverage.py interval_interpolate.bed value_interpolate.bed interpolate_result.bed
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20
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21 def stop_err(msg):
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22 sys.stderr.write(msg)
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23 sys.exit()
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24
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25
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26 def FindRate(chromosome, start_stop, dictType):
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27 OverlapList = []
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28 for tempO in dictType[chromosome]:
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29 DatabaseInterval = [tempO[0], tempO[1]]
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30 Overlap = GetOverlap( start_stop, DatabaseInterval )
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31 if Overlap > 0:
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32 OverlapList.append([Overlap, tempO[2]])
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33
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34 if len(OverlapList) > 0:
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35 SumRecomb = 0
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36 SumOverlap = 0
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37 for member in OverlapList:
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38 SumRecomb += member[0]*member[1]
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39 SumOverlap += member[0]
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40 averageRate = SumRecomb/SumOverlap
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41 return averageRate
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42 else:
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43 return 'NA'
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44
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45
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46 def GetOverlap(a, b):
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47 return min(a[1], b[1])-max(a[0], b[0])
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48
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49
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50 options, args = doc_optparse.parse( __doc__ )
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51
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52 try:
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53 chr_col_1, start_col_1, end_col_1, strand_col1 = parse_cols_arg( options.cols1 )
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54 chr_col_2, start_col_2, end_col_2, strand_col2, name_col_2 = parse_cols_arg( options.cols2 )
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55 input1, input2, input3 = args
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56 except Exception, eee:
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57 print eee
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58 stop_err( "Data issue: click the pencil icon in the history item to correct the metadata attributes." )
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59
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60 fd2 = open(input2)
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61 lines2 = fd2.readlines()
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62 RecombChrDict = collections.defaultdict(list)
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63
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64 skipped = 0
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65 for line in lines2:
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66 temp = line.strip().split()
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67 try:
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68 assert float(temp[int(name_col_2)])
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69 except:
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70 skipped += 1
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71 continue
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72 tempIndex = [int(temp[int(start_col_2)]), int(temp[int(end_col_2)]), float(temp[int(name_col_2)])]
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73 RecombChrDict[temp[int(chr_col_2)]].append(tempIndex)
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74
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75 print "Skipped %d features with invalid values" % (skipped)
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76
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77 fd1 = open(input1)
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78 lines = fd1.readlines()
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79 finalProduct = ''
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80 for line in lines:
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81 temp = line.strip().split('\t')
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82 chromosome = temp[int(chr_col_1)]
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83 start = int(temp[int(start_col_1)])
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84 stop = int(temp[int(end_col_1)])
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85 start_stop = [start, stop]
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86 RecombRate = FindRate( chromosome, start_stop, RecombChrDict )
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87 try:
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88 RecombRate = "%.4f" % (float(RecombRate))
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89 except:
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90 RecombRate = RecombRate
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91 finalProduct += line.strip()+'\t'+str(RecombRate)+'\n'
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92 fdd = open(input3, 'w')
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93 fdd.writelines(finalProduct)
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94 fdd.close()
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