Mercurial > repos > artbio > small_rna_maps

annotate small_rna_maps.py @ 16:600e2498bd21 draft

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 82bb0971cde6ba1972588c9315c3007bc3a5a6a7-dirty
author artbio
date Tue, 13 Nov 2018 17:03:46 -0500
parents 82fedc576024
children b28dcd4051e8
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
artbio
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1 import argparse
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
artbio
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2 from collections import defaultdict
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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4 import numpy
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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6 import pysam
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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9 def Parser():
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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10 the_parser = argparse.ArgumentParser()
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11 the_parser.add_argument('--inputs', dest='inputs', required=True,
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12 nargs='+', help='list of input BAM files')
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13 the_parser.add_argument('--minsize', dest='minsize', type=int,
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14 default=0, help='minimal size of reads')
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15 the_parser.add_argument('--maxsize', dest='maxsize', type=int,
1827b74f872b planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit e4588eb6c329e4516e9bcfa084a383be81b55c60
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16 default=10000, help='maximal size of reads')
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17 the_parser.add_argument('--cluster', dest='cluster', type=int,
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18 default=0, help='clustering distance')
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19 the_parser.add_argument('--sample_names', dest='sample_names',
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20 required=True, nargs='+',
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21 help='list of sample names')
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22 the_parser.add_argument('--outputs', nargs='+', action='store',
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23 help='list of two output paths (only two)')
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24 the_parser.add_argument('-M', '--plot_methods', nargs='+', action='store',
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25 help='list of 2 plot methods (only two) among:\
507383cce5a8 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit edbb53cb13b52bf8e71c562fa8acc2c3be2fb270
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26 Counts, Max, Mean, Median, Coverage and Size')
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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27 args = the_parser.parse_args()
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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28 return args
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31 class Map:
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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32
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33 def __init__(self, bam_file, sample, minsize, maxsize, cluster):
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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34 self.sample_name = sample
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35 self.minsize = minsize
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36 self.maxsize = maxsize
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37 self.cluster = cluster
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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38 self.bam_object = pysam.AlignmentFile(bam_file, 'rb')
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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39 self.chromosomes = dict(zip(self.bam_object.references,
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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40 self.bam_object.lengths))
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41 self.map_dict = self.create_map(self.bam_object, self.minsize,
1827b74f872b planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit e4588eb6c329e4516e9bcfa084a383be81b55c60
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42 self.maxsize)
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43 if self.cluster:
3ea75c573429 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 6199193c7fe2cb56403eea8af0b40d44f7311fd5
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44 self.map_dict = self.tile_map(self.map_dict, self.cluster)
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45
8
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46 def create_map(self, bam_object, minsize, maxsize):
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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47 '''
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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48 Returns a map_dictionary {(chromosome,read_position,polarity):
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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49 [read_length, ...]}
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50 '''
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51 map_dictionary = defaultdict(list)
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52 for chrom in self.chromosomes:
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53 # get empty value for start and end of each chromosome
0
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54 map_dictionary[(chrom, 1, 'F')] = []
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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55 map_dictionary[(chrom, self.chromosomes[chrom], 'F')] = []
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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56 for read in bam_object.fetch(chrom):
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57 positions = read.positions # a list of covered positions
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58 if read.is_reverse:
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59 map_dictionary[(chrom, positions[-1]+1, 'R')].append(
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60 read.query_alignment_length)
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61 else:
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62 map_dictionary[(chrom, positions[0]+1, 'F')].append(
82fedc576024 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit c1d96f7f028512aa4d8fcae3dd5f967cd445708e
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63 read.query_alignment_length)
0
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64 return map_dictionary
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65
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66 def grouper(self, iterable, clust_distance):
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67 prev = None
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68 group = []
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69 for item in iterable:
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70 if not prev or item - prev <= clust_distance:
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71 group.append(item)
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72 else:
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73 yield group
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74 group = [item]
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75 prev = item
3ea75c573429 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 6199193c7fe2cb56403eea8af0b40d44f7311fd5
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76 if group:
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77 yield group
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78
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79 def tile_map(self, map_dic, clust_distance):
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80 '''
3ea75c573429 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 6199193c7fe2cb56403eea8af0b40d44f7311fd5
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81 takes a map_dictionary {(chromosome,read_position,polarity):
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82 [read_length, ...]}
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83 and returns a map_dictionary with structure:
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84 {(chromosome,read_position,polarity):
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85 ([read_length, ...], [start_clust, end_clust])}
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86 '''
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87 clustered_dic = defaultdict(list)
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88 for chrom in self.chromosomes:
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89 F_chrom_coord = []
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90 R_chrom_coord = []
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91 for key in map_dic:
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92 if key[0] == chrom and key[2] == 'F':
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93 F_chrom_coord.append(key[1])
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94 elif key[0] == chrom and key[2] == 'R':
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95 R_chrom_coord.append(key[1])
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96 F_chrom_coord = list(set(F_chrom_coord))
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97 R_chrom_coord = list(set(R_chrom_coord))
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98 F_chrom_coord.sort()
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99 R_chrom_coord.sort()
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100 F_clust_values = [i for i in self.grouper(F_chrom_coord,
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101 clust_distance)]
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102 F_clust_keys = [(i[-1]+i[0])/2 for i in F_clust_values]
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103 R_clust_values = [i for i in self.grouper(R_chrom_coord,
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104 clust_distance)]
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105 R_clust_keys = [(i[-1]+i[0])/2 for i in R_clust_values]
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106 # now 2 dictionnaries (F and R) with structure:
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107 # {centered_coordinate: [coord1, coord2, coord3, ..]}
9
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108 F_clust_dic = dict(zip(F_clust_keys, F_clust_values))
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109 R_clust_dic = dict(zip(R_clust_keys, R_clust_values))
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110 for centcoor in F_clust_dic:
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111 accumulator = []
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112 for coor in F_clust_dic[centcoor]:
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113 accumulator.extend(map_dic[(chrom, coor, 'F')])
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114 clustered_dic[(chrom, centcoor, 'F')] = [len(accumulator), [
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115 F_clust_dic[centcoor][0],
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116 F_clust_dic[centcoor][-1]]]
9
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117 for centcoor in R_clust_dic:
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118 accumulator = []
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119 for coor in R_clust_dic[centcoor]:
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120 accumulator.extend(map_dic[(chrom, coor, 'R')])
16
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121 clustered_dic[(chrom, centcoor, 'R')] = [len(accumulator), [
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122 R_clust_dic[centcoor][0],
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123 R_clust_dic[centcoor][-1]]]
9
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124 return clustered_dic
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125
3
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126 def compute_readcount(self, map_dictionary, out):
2
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127 '''
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128 takes a map_dictionary as input and writes
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129 a readmap_dictionary {(chromosome,read_position,polarity):
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130 number_of_reads}
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131 in an open file handler out
0
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132 '''
2
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133 readmap_dictionary = dict()
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134 for key in map_dictionary:
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135 readmap_dictionary[key] = len(map_dictionary[key])
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136 self.write_table(readmap_dictionary, out)
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137
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138 def compute_max(self, map_dictionary, out):
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139 '''
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140 takes a map_dictionary as input and writes
0
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141 a max_dictionary {(chromosome,read_position,polarity):
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142 max_of_number_of_read_at_any_position}
2
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143 Not clear this function is still required
0
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144 '''
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145 merge_keylist = [(i[0], 0) for i in map_dictionary.keys()]
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146 max_dictionary = dict(merge_keylist)
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147 for key in map_dictionary:
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148 if len(map_dictionary[key]) > max_dictionary[key[0]]:
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149 max_dictionary[key[0]] = len(map_dictionary[key])
2
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150 self.write_table(max_dictionary, out)
0
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151
2
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152 def compute_mean(self, map_dictionary, out):
0
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153 '''
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154 takes a map_dictionary as input and returns
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155 a mean_dictionary {(chromosome,read_position,polarity):
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156 mean_value_of_reads}
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157 '''
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158 mean_dictionary = dict()
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159 for key in map_dictionary:
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160 if len(map_dictionary[key]) == 0:
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161 mean_dictionary[key] = 0
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162 else:
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163 mean_dictionary[key] = round(numpy.mean(map_dictionary[key]),
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164 1)
2
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165 self.write_table(mean_dictionary, out)
0
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166
2
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167 def compute_median(self, map_dictionary, out):
0
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168 '''
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169 takes a map_dictionary as input and returns
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170 a mean_dictionary {(chromosome,read_position,polarity):
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171 mean_value_of_reads}
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172 '''
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173 median_dictionary = dict()
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174 for key in map_dictionary:
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175 if len(map_dictionary[key]) == 0:
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176 median_dictionary[key] = 0
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177 else:
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178 median_dictionary[key] = numpy.median(map_dictionary[key])
2
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179 self.write_table(median_dictionary, out)
0
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180
16
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181 def compute_coverage(self, map_dictionary, out, quality=15):
0
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182 '''
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diff changeset
183 takes a map_dictionary as input and returns
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184 a coverage_dictionary {(chromosome,read_position,polarity):
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185 coverage}
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186 '''
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artbio
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187 coverage_dictionary = dict()
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188 for chrom in self.chromosomes:
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189 coverage_dictionary[(chrom, 1, 'F')] = 0
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artbio
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190 coverage_dictionary[(chrom, self.chromosomes[chrom], 'F')] = 0
4
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191 for read in self.bam_object.fetch(chrom):
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192 positions = read.positions # a list of covered positions
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193 for pos in positions:
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194 if not map_dictionary[(chrom, pos+1, 'F')]:
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195 map_dictionary[(chrom, pos+1, 'F')] = []
0
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196 for key in map_dictionary:
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197 coverage = self.bam_object.count_coverage(
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198 reference=key[0],
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199 start=key[1]-1,
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200 end=key[1],
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201 quality_threshold=quality)
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202 """ Add the 4 coverage values """
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203 coverage = [sum(x) for x in zip(*coverage)]
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204 coverage_dictionary[key] = coverage[0]
2
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205 self.write_table(coverage_dictionary, out)
0
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206
2
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207 def compute_size(self, map_dictionary, out):
0
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208 '''
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artbio
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diff changeset
209 Takes a map_dictionary and returns a dictionary of sizes:
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210 {chrom: {polarity: {size: nbre of reads}}}
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211 '''
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artbio
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212 size_dictionary = defaultdict(lambda: defaultdict(
1
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artbio
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213 lambda: defaultdict(int)))
0
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214 # to track empty chromosomes
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artbio
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215 for chrom in self.chromosomes:
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216 if self.bam_object.count(chrom) == 0:
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artbio
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217 size_dictionary[chrom]['F'][10] = 0
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artbio
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218 for key in map_dictionary:
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artbio
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219 for size in map_dictionary[key]:
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artbio
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220 size_dictionary[key[0]][key[2]][size] += 1
2
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diff changeset
221 self.write_size_table(size_dictionary, out)
0
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diff changeset
222
2
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diff changeset
223 def write_table(self, mapdict, out):
0
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224 '''
16
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diff changeset
225 Writer of a tabular file
2
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diff changeset
226 Dataset, Chromosome, Chrom_length, Coordinate, Polarity,
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diff changeset
227 <some mapped value>
0
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228 out is an *open* file handler
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229 '''
2
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diff changeset
230 for key in sorted(mapdict):
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231 line = [self.sample_name, key[0], self.chromosomes[key[0]],
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232 key[1], key[2], mapdict[key]]
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diff changeset
233 line = [str(i) for i in line]
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diff changeset
234 out.write('\t'.join(line) + '\n')
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diff changeset
235
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diff changeset
236 def write_size_table(self, sizedic, out):
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237 '''
16
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diff changeset
238 Writer of a tabular file
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artbio
parents: 15
diff changeset
239 Dataset, Chromosome, Chrom_length, <category (size)>, <some value>
2
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diff changeset
240 out is an *open* file handler
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artbio
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diff changeset
241 '''
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artbio
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diff changeset
242 for chrom in sorted(sizedic):
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artbio
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diff changeset
243 sizes = sizedic[chrom]['F'].keys()
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diff changeset
244 sizes.extend(sizedic[chrom]['R'].keys())
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artbio
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diff changeset
245 for polarity in sorted(sizedic[chrom]):
0
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artbio
parents:
diff changeset
246 for size in range(min(sizes), max(sizes)+1):
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artbio
parents:
diff changeset
247 try:
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artbio
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diff changeset
248 line = [self.sample_name, chrom, polarity, size,
2
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diff changeset
249 sizedic[chrom][polarity][size]]
0
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artbio
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diff changeset
250 except KeyError:
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artbio
parents:
diff changeset
251 line = [self.sample_name, chrom, polarity, size, 0]
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artbio
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diff changeset
252 line = [str(i) for i in line]
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artbio
parents:
diff changeset
253 out.write('\t'.join(line) + '\n')
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diff changeset
254
16
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diff changeset
255 def write_cluster_table(self, clustered_dic, out):
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diff changeset
256 '''
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artbio
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diff changeset
257 Writer of a tabular file
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artbio
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diff changeset
258 Dataset, Chromosome, Chrom_length, Coordinate, Polarity,
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artbio
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diff changeset
259 <some mapped value>
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artbio
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diff changeset
260 out is an *open* file handler
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diff changeset
261 '''
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262 for key in sorted(clustered_dic):
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263 start = clustered_dic[key][1][0]
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264 end = clustered_dic[key][1][1]
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265 size = end - start + 1
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266 density = float(clustered_dic[key][0]) / size
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267 line = [self.sample_name, key[0], self.chromosomes[key[0]],
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268 key[1], key[2], clustered_dic[key][0],
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269 str(start) + "-" + str(end), str(size), str(density)]
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270 line = [str(i) for i in line]
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271 out.write('\t'.join(line) + '\n')
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272
0
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273
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274 def main(inputs, samples, methods, outputs, minsize, maxsize, cluster):
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275 for method, output in zip(methods, outputs):
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276 out = open(output, 'w')
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277 if method == 'Size':
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278 header = ["Dataset", "Chromosome", "Polarity", method, "Counts"]
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279 elif cluster:
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280 header = ["Dataset", "Chromosome", "Chrom_length", "Coordinate",
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281 "Polarity", method, "Start-End", "Cluster Size",
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282 "density"]
2
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283 else:
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284 header = ["Dataset", "Chromosome", "Chrom_length", "Coordinate",
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285 "Polarity", method]
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286 out.write('\t'.join(header) + '\n')
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287 for input, sample in zip(inputs, samples):
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288 mapobj = Map(input, sample, minsize, maxsize, cluster)
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289 token = {"Counts": mapobj.compute_readcount,
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290 "Max": mapobj.compute_max,
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291 "Mean": mapobj.compute_mean,
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292 "Median": mapobj.compute_median,
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293 "Coverage": mapobj.compute_coverage,
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294 "Size": mapobj.compute_size,
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295 "cluster": mapobj.write_cluster_table}
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296 if cluster:
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297 token["cluster"](mapobj.map_dict, out)
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298 else:
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299 token[method](mapobj.map_dict, out)
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300 # mapobj.compute_coverage(mapobj.map_dict, out)
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301 out.close()
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302
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303
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304 if __name__ == "__main__":
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305 args = Parser()
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306 # if identical sample names
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307 if len(set(args.sample_names)) != len(args.sample_names):
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308 args.sample_names = [name + '_' + str(i) for
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309 i, name in enumerate(args.sample_names)]
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310 main(args.inputs, args.sample_names, args.plot_methods, args.outputs,
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311 args.minsize, args.maxsize, args.cluster)