Mercurial > repos > artbio > small_rna_map

annotate small_rna_map.py @ 7:35d3f8ac99cf draft

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 975e2303944d19a4124210741e5a0d1feb546e45
author artbio
date Sun, 23 Jul 2017 05:21:58 -0400
parents f924a33e1eef
children 2cc2948cfa34
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2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
artbio
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1 import argparse
2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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2 from collections import defaultdict
2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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4 import numpy
2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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1ad5d040f85f planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit fa452d860cf550c7524df59e77b36fd39e3e2a45
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6 import pysam
1ad5d040f85f planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit fa452d860cf550c7524df59e77b36fd39e3e2a45
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9 def Parser():
1ad5d040f85f planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit fa452d860cf550c7524df59e77b36fd39e3e2a45
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10 the_parser = argparse.ArgumentParser()
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2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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11 the_parser.add_argument('--input', dest='input', required=True,
2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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12 nargs='+', help='input BAM files')
2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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13 the_parser.add_argument('--sample_name', dest='sample_name',
2e0dc6032a98 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
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14 required=True, nargs='+', help='sample name')
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15 the_parser.add_argument('--output', action='store',
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16 type=str, help='output tabular file')
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17 the_parser.add_argument('-S', '--sizes', action='store',
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18 help='use to output read sizes dataframe')
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19 args = the_parser.parse_args()
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20 return args
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23 class Map:
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25 def __init__(self, bam_file, sample, computeSize=False):
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26 self.sample_name = sample
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27 self.bam_object = pysam.AlignmentFile(bam_file, 'rb')
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28 self.chromosomes = dict(zip(self.bam_object.references,
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29 self.bam_object.lengths))
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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30 self.map_dict = self.create_map(self.bam_object)
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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31 self.max = self.compute_max(self.map_dict)
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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32 self.mean = self.compute_mean(self.map_dict)
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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33 self.median = self.compute_median(self.map_dict)
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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34 self.coverage = self.compute_coverage(self.map_dict)
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35 if computeSize:
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36 self.size = self.compute_size(self.map_dict)
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38 def create_map(self, bam_object):
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39 '''
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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40 Returns a map_dictionary {(chromosome,read_position,polarity):
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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41 [read_length, ...]}
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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42 '''
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43 map_dictionary = dict()
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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44 for chrom in self.chromosomes:
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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45 for pos in range(self.chromosomes[chrom]):
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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46 map_dictionary[(chrom, pos+1, 'F')] = [] # get all chromosomes
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47 map_dictionary[(chrom, pos+1, 'R')] = [] # get all chromosomes
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48 for chrom in self.chromosomes:
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49 for read in bam_object.fetch(chrom):
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50 read_positions = read.positions # a list of covered positions
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51 if read.is_reverse:
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52 map_dictionary[(chrom, read_positions[-1]+1,
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53 'R')].append(read.query_alignment_length)
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54 else:
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55 map_dictionary[(chrom, read_positions[0]+1,
d65045e976e6 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit b673d39fbe79f5164ba6489b33cfa78ac238ee09
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56 'F')].append(read.query_alignment_length)
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57 return map_dictionary
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58
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59 def compute_max(self, map_dictionary):
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60 '''
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61 takes a map_dictionary as input and returns
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62 a max_dictionary {(chromosome,read_position,polarity):
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63 max_of_number_of_read_at_any_position}
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64 '''
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65 merge_keylist = [(i[0], 0) for i in map_dictionary.keys()]
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66 max_dictionary = dict(merge_keylist)
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67 for key in map_dictionary:
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68 if len(map_dictionary[key]) > max_dictionary[key[0]]:
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69 max_dictionary[key[0]] = len(map_dictionary[key])
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70 return max_dictionary
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71
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72 def compute_mean(self, map_dictionary):
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73 '''
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74 takes a map_dictionary as input and returns
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75 a mean_dictionary {(chromosome,read_position,polarity):
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76 mean_value_of_reads}
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77 '''
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78 mean_dictionary = dict()
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79 for key in map_dictionary:
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80 if len(map_dictionary[key]) == 0:
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81 mean_dictionary[key] = 0
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82 else:
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83 mean_dictionary[key] = round(numpy.mean(map_dictionary[key]),
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84 1)
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85 return mean_dictionary
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86
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87 def compute_median(self, map_dictionary):
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88 '''
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89 takes a map_dictionary as input and returns
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90 a mean_dictionary {(chromosome,read_position,polarity):
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91 mean_value_of_reads}
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92 '''
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93 median_dictionary = dict()
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94 for key in map_dictionary:
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95 if len(map_dictionary[key]) == 0:
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96 median_dictionary[key] = 0
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97 else:
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98 median_dictionary[key] = numpy.median(map_dictionary[key])
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99 return median_dictionary
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100
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101 def compute_coverage(self, map_dictionary, quality=10):
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102 '''
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103 Takes a map_dictionary and returns a dictionary of lists
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104 of coverage along the coordinates of pre_mirs (as keys)
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105 '''
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106 coverage_dictionary = dict()
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107 for chrom in self.chromosomes:
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108 coverage = self.bam_object.count_coverage(
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109 reference=chrom,
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110 start=0,
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111 end=self.chromosomes[chrom],
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112 quality_threshold=quality)
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113 """ Add the 4 coverage values """
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114 coverage = [sum(x) for x in zip(*coverage)]
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115 for pos, cov in enumerate(coverage):
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116 coverage_dictionary[(chrom, pos+1, "F")] = cov
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117 coverage_dictionary[(chrom, pos+1, "R")] = cov
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118 return coverage_dictionary
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119
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120 def compute_size(self, map_dictionary):
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121 '''
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122 Takes a map_dictionary and returns a dictionary of sizes:
7
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123 {chrom: {polarity: {size: nbre of reads}}}
5
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124 '''
6
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125 size_dictionary = defaultdict(lambda: defaultdict(
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126 lambda: defaultdict( int )))
7
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127 # to track empty chromosomes
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128 for chrom in self.chromosomes:
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129 if self.bam_object.count(chrom) == 0:
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130 size_dictionary[chrom]['F'][10] = 0
5
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131 for key in map_dictionary:
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132 for size in map_dictionary[key]:
6
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133 size_dictionary[key[0]][key[2]][size] += 1
5
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134 return size_dictionary
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135
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136 def write_size_table(self, out):
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137 '''
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138 Dataset, Chromosome, Polarity, Size, Nbr_reads
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139 out is an *open* file handler
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140 '''
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141 for chrom in sorted(self.size):
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142 sizes = self.size[chrom]['F'].keys()
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143 sizes.extend(self.size[chrom]['R'].keys())
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144 for polarity in sorted(self.size[chrom]):
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145 for size in range(min(sizes), max(sizes)+1):
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146 try:
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147 line = [self.sample_name, chrom, polarity, size,
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148 self.size[chrom][polarity][size]]
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149 except KeyError:
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150 line = [self.sample_name, chrom, polarity, size, 0]
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151 line = [str(i) for i in line]
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152 out.write('\t'.join(line) + '\n')
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153
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154 def write_table(self, out):
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155 '''
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diff changeset
156 Dataset, Chromosome, Chrom_length, Coordinate, Nbr_reads
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157 Polarity, Max, Mean, Median, Coverage
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158 out is an *open* file handler
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159 '''
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diff changeset
160 for key in sorted(self.map_dict):
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161 line = [self.sample_name, key[0], self.chromosomes[key[0]],
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162 key[1], len(self.map_dict[key]), key[2], self.max[key[0]],
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163 self.mean[key], self.median[key], self.coverage[key]]
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164 line = [str(i) for i in line]
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165 out.write('\t'.join(line) + '\n')
0
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166
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167
5
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168 def main(inputs, samples, file_out, size_file_out=''):
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169 F = open(file_out, 'w')
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170 header = ["Dataset", "Chromosome", "Chrom_length", "Coordinate",
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171 "Nbr_reads", "Polarity", "Max", "Mean", "Median", "Coverage"]
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172 F.write('\t'.join(header) + '\n')
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diff changeset
173 if size_file_out:
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174 Fs = open(size_file_out, 'w')
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175 header = ["Dataset", "Chromosome", "Polarity", "Size", "Nbr_reads"]
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diff changeset
176 Fs.write('\t'.join(header) + '\n')
7
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177 for file, sample in zip(inputs, samples):
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178 mapobj = Map(file, sample, computeSize=True)
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179 mapobj.write_table(F)
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180 mapobj.write_size_table(Fs)
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181 Fs.close()
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182 else:
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183 for file, sample in zip(inputs, samples):
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184 mapobj = Map(file, sample, computeSize=False)
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185 mapobj.write_table(F)
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186 F.close()
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187
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188
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189 if __name__ == "__main__":
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190 args = Parser()
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191 # if identical sample names
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192 if len(set(args.sample_name)) != len(args.sample_name):
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193 args.sample_name = [name + '_' + str(i) for
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194 i, name in enumerate(args.sample_name)]
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195 main(args.input, args.sample_name, args.output, args.sizes)