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1 #!/usr/bin/python
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2 # python parser module for size distributions, guided by GFF3
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3 # version 0.9.1 (1-6-2014)
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4 # Usage readmap.py <1:index source> <2:extraction directive> <3:output pre-mir> <4: output mature miRs> <5:mirbase GFF3>
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5 # <6:pathToLatticeDataframe or "dummy_dataframe_path"> <7:Rcode or "dummy_plotCode"> <8:latticePDF or "dummy_latticePDF">
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6 # <9:10:11 filePath:FileExt:FileLabel> <.. ad lib>
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7
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8 import sys, subprocess, argparse
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9 from smRtools import *
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10 from collections import OrderedDict, defaultdict
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11 import os
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12
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13 def Parser():
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14 the_parser = argparse.ArgumentParser()
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15 the_parser.add_argument('--output_size_distribution', action="store", type=str, help="size distribution dataframe")
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16 the_parser.add_argument('--reference_fasta', action="store", type=str, help="output file")
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17 the_parser.add_argument('--reference_bowtie_index',action='store', help="paths to indexed or fasta references")
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18 the_parser.add_argument('--input',nargs='+', help="paths to multiple input files")
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19 the_parser.add_argument('--ext',nargs='+', help="input file type")
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20 the_parser.add_argument('--label',nargs='+', help="labels of multiple input files")
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21 the_parser.add_argument('--normalization_factor',nargs='+', type=float, help="Normalization factor for input file")
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22 the_parser.add_argument('--gff', type=str, help="GFF containing regions of interest")
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23 the_parser.add_argument('--minquery', type=int, help="Minimum readsize")
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24 the_parser.add_argument('--maxquery', type=int, help="Maximum readsize")
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25 the_parser.add_argument('--rcode', type=str, help="R script")
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26 the_parser.add_argument('--global_size', action="store_true", help="if specified, size distribution is calcilated for the sum of all items")
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27 the_parser.add_argument('--collapse', action="store_true", help="if specified, forward and reverse reads are collapsed")
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28 args = the_parser.parse_args()
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29 return args
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30
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31 args=Parser()
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32 if args.reference_fasta:
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33 genomeRefFormat = "fastaSource"
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34 genomeRefFile = args.reference_fasta
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35 if args.reference_bowtie_index:
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36 genomeRefFormat = "bowtieIndex"
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37 genomeRefFile = args.reference_bowtie_index
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38 size_distribution_file=args.output_size_distribution
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39 minquery=args.minquery
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40 maxquery=args.maxquery
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41 Rcode = args.rcode
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42 filePath=args.input
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43 fileExt=args.ext
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44 fileLabel=args.label
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45 normalization_factor=args.normalization_factor
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46 global_size=args.global_size
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47 collapse=args.collapse
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48
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49 if collapse:
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50 pol=["both"]
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51 else:
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52 pol=["F", "R"]
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53
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54 MasterListOfGenomes = OrderedDict()
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55
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56 def process_samples(filePath):
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57 for i, filePath in enumerate(filePath):
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58 norm=normalization_factor[i]
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59 print fileLabel[i]
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60 MasterListOfGenomes[fileLabel[i]] = HandleSmRNAwindows (alignmentFile=filePath, alignmentFileFormat=fileExt[i], genomeRefFile=genomeRefFile, genomeRefFormat=genomeRefFormat,\
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61 biosample=fileLabel[i], size_inf=minquery, size_sup=maxquery, norm=norm)
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62 return MasterListOfGenomes
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63
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64 def write_size_distribution_dataframe(readDict, size_distribution_file, pol=["both"] ):
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65 '''refactored on 7-9-2014'''
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66 with open(size_distribution_file, 'w') as size_distrib:
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67 print >>size_distrib, "gene\tpolarity\tsize\tcount\tsample"
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68 for sample in readDict.keys():
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69 if args.gff:
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70 dict=readDict[sample]
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71 else:
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72 dict=readDict[sample].instanceDict
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73 for gene in dict.keys():
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74 histogram = dict[gene].size_histogram()
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75 for polarity in pol:
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76 for size, count in histogram[polarity].iteritems():
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77 print >>size_distrib, "%s\t%s\t%s\t%s\t%s" % (gene, polarity, size, count, sample)
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78
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79 def write_size_distribution_dataframe_global(readDict, size_distribution_file, pol=["both"]):
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80 with open(size_distribution_file, 'w') as size_distrib:
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81 print >>size_distrib, "gene\tpolarity\tsize\tcount\tsample"
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82 for sample in readDict.keys():
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83 histogram = readDict[sample].size_histogram()
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84 gene="sample"
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85 for polarity in pol:
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86 for size, count in histogram[polarity].iteritems():
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87 print >>size_distrib, "%s\t%s\t%s\t%s\t%s" % (gene, polarity, size, count, sample)
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88
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89 def gff_item_subinstances(readDict, gff3):
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90 GFFinstanceDict=OrderedDict()
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91 with open(gff3) as gff:
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92 for line in gff:
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93 if line[0] == "#": continue
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94 gff_fields = line[:-1].split("\t")
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95 chrom = gff_fields[0]
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96 gff_name = gff_fields[-1].split("Name=")[-1].split(";")[0] # to isolate the GFF Name
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97 item_upstream_coordinate = int(gff_fields[3])
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98 item_downstream_coordinate = int(gff_fields[4])
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99 item_polarity = gff_fields[6]
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100 for sample in readDict.keys():
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101 if not GFFinstanceDict.has_key(sample):
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102 GFFinstanceDict[sample]={}
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103 subinstance=extractsubinstance(item_upstream_coordinate, item_downstream_coordinate, readDict[sample].instanceDict[chrom])
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104 if item_polarity == '-':
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105 subinstance.readDict={key*-1:value for key, value in subinstance.readDict.iteritems()}
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106 # subinstance.readDict.setdefault(key, [])
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107 subinstance.gene=gff_name
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108 GFFinstanceDict[sample][gff_name]=subinstance
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109 return GFFinstanceDict
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110
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111 MasterListOfGenomes=process_samples(filePath)
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112
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113 if args.gff:
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114 MasterListOfGenomes=gff_item_subinstances(MasterListOfGenomes, args.gff)
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115
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116 if global_size:
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117 write_size_distribution_dataframe_global(MasterListOfGenomes, size_distribution_file, pol)
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118 else:
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119 write_size_distribution_dataframe(MasterListOfGenomes, size_distribution_file, pol)
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120
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121 R_command="Rscript "+ Rcode
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122 process = subprocess.Popen(R_command.split())
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123 process.wait()
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124
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125
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