annotate small_rna_maps.py @ 11:a561a71bd7d7 draft

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit c24bbb6d53574eb1c1eb8d219cf2a39a9ed5b3ff
author artbio
date Tue, 06 Mar 2018 06:11:55 -0500
parents 3ea75c573429
children 82fedc576024
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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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1 import argparse
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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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
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6 import pysam
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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,
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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='+',
507383cce5a8 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit edbb53cb13b52bf8e71c562fa8acc2c3be2fb270
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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:\
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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()
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28 return args
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31 class Map:
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32
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33 def __init__(self, bam_file, sample, minsize, maxsize, cluster):
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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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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:
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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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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 '''
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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51 map_dictionary = defaultdict(list)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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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
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54 map_dictionary[(chrom, 1, 'F')] = []
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55 map_dictionary[(chrom, self.chromosomes[chrom], 'F')] = []
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56 for read in bam_object.fetch(chrom):
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57 if (read.query_alignment_length >= minsize and
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58 read.query_alignment_length <= maxsize):
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59 positions = read.positions # a list of covered positions
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60 if read.is_reverse:
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61 map_dictionary[(chrom, positions[-1]+1, 'R')].append(
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62 read.query_alignment_length)
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63 else:
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64 map_dictionary[(chrom, positions[0]+1, 'F')].append(
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65 read.query_alignment_length)
0
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66 return map_dictionary
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67
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68 def grouper(self, iterable, clust_distance):
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69 prev = None
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70 group = []
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71 for item in iterable:
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72 if not prev or item - prev <= clust_distance:
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73 group.append(item)
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74 else:
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75 yield group
3ea75c573429 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 6199193c7fe2cb56403eea8af0b40d44f7311fd5
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76 group = [item]
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77 prev = item
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78 if group:
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79 yield group
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80
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81 def tile_map(self, map_dic, clust_distance):
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82 '''
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83 takes a map_dictionary {(chromosome,read_position,polarity):
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84 [read_length, ...]}
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85 and retur a map_dictionary with same structure but with
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86 read positions aggregated by size
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87 '''
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88 clustered_dic = defaultdict(list)
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89 for chrom in self.chromosomes:
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90 clustered_dic[(chrom, 1, 'F')] = []
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91 clustered_dic[(chrom, self.chromosomes[chrom], 'F')] = []
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92 F_chrom_coord = []
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93 R_chrom_coord = []
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94 for key in map_dic:
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95 if key[0] == chrom and key[2] == 'F':
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96 F_chrom_coord.append(key[1])
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97 elif key[0] == chrom and key[2] == 'R':
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98 R_chrom_coord.append(key[1])
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99 F_chrom_coord = list(set(F_chrom_coord))
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100 R_chrom_coord = list(set(R_chrom_coord))
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101 F_chrom_coord.sort()
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102 R_chrom_coord.sort()
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103 F_clust_values = [i for i in self.grouper(F_chrom_coord,
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104 clust_distance)]
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105 F_clust_keys = [(i[-1]+i[0])/2 for i in F_clust_values]
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106 R_clust_values = [i for i in self.grouper(R_chrom_coord,
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107 clust_distance)]
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108 R_clust_keys = [(i[-1]+i[0])/2 for i in R_clust_values]
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109 F_clust_dic = dict(zip(F_clust_keys, F_clust_values))
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110 R_clust_dic = dict(zip(R_clust_keys, R_clust_values))
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111 # {centered_coordinate: [coord1, coord2, coord3, ..]}
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112 for centcoor in F_clust_dic:
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113 accumulator = []
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114 for coor in F_clust_dic[centcoor]:
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115 accumulator.extend(map_dic[(chrom, coor, 'F')])
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116 clustered_dic[(chrom, centcoor, 'F')] = accumulator
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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')])
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121 clustered_dic[(chrom, centcoor, 'R')] = accumulator
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122 return clustered_dic
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123
3
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124 def compute_readcount(self, map_dictionary, out):
2
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125 '''
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126 takes a map_dictionary as input and writes
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127 a readmap_dictionary {(chromosome,read_position,polarity):
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128 number_of_reads}
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129 in an open file handler out
0
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130 '''
2
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131 readmap_dictionary = dict()
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132 for key in map_dictionary:
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133 readmap_dictionary[key] = len(map_dictionary[key])
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134 self.write_table(readmap_dictionary, out)
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135
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136 def compute_max(self, map_dictionary, out):
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137 '''
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138 takes a map_dictionary as input and writes
0
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139 a max_dictionary {(chromosome,read_position,polarity):
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140 max_of_number_of_read_at_any_position}
2
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141 Not clear this function is still required
0
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142 '''
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143 merge_keylist = [(i[0], 0) for i in map_dictionary.keys()]
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144 max_dictionary = dict(merge_keylist)
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145 for key in map_dictionary:
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146 if len(map_dictionary[key]) > max_dictionary[key[0]]:
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147 max_dictionary[key[0]] = len(map_dictionary[key])
2
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148 self.write_table(max_dictionary, out)
0
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149
2
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150 def compute_mean(self, map_dictionary, out):
0
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151 '''
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152 takes a map_dictionary as input and returns
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153 a mean_dictionary {(chromosome,read_position,polarity):
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154 mean_value_of_reads}
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155 '''
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156 mean_dictionary = dict()
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157 for key in map_dictionary:
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158 if len(map_dictionary[key]) == 0:
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159 mean_dictionary[key] = 0
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160 else:
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161 mean_dictionary[key] = round(numpy.mean(map_dictionary[key]),
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162 1)
2
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163 self.write_table(mean_dictionary, out)
0
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164
2
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165 def compute_median(self, map_dictionary, out):
0
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166 '''
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167 takes a map_dictionary as input and returns
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168 a mean_dictionary {(chromosome,read_position,polarity):
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169 mean_value_of_reads}
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170 '''
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171 median_dictionary = dict()
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172 for key in map_dictionary:
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173 if len(map_dictionary[key]) == 0:
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174 median_dictionary[key] = 0
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175 else:
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176 median_dictionary[key] = numpy.median(map_dictionary[key])
2
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diff changeset
177 self.write_table(median_dictionary, out)
0
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178
2
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diff changeset
179 def compute_coverage(self, map_dictionary, out, quality=10):
0
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180 '''
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artbio
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diff changeset
181 takes a map_dictionary as input and returns
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artbio
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182 a coverage_dictionary {(chromosome,read_position,polarity):
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artbio
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diff changeset
183 coverage}
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artbio
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184 '''
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artbio
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185 coverage_dictionary = dict()
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artbio
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186 for chrom in self.chromosomes:
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artbio
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187 coverage_dictionary[(chrom, 1, 'F')] = 0
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artbio
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188 coverage_dictionary[(chrom, self.chromosomes[chrom], 'F')] = 0
4
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artbio
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189 for read in self.bam_object.fetch(chrom):
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artbio
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190 positions = read.positions # a list of covered positions
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artbio
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191 for pos in positions:
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artbio
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192 if not map_dictionary[(chrom, pos+1, 'F')]:
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artbio
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193 map_dictionary[(chrom, pos+1, 'F')] = []
0
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artbio
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194 for key in map_dictionary:
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artbio
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195 coverage = self.bam_object.count_coverage(
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artbio
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196 reference=key[0],
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artbio
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197 start=key[1]-1,
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artbio
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198 end=key[1],
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artbio
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199 quality_threshold=quality)
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artbio
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200 """ Add the 4 coverage values """
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artbio
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201 coverage = [sum(x) for x in zip(*coverage)]
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artbio
parents:
diff changeset
202 coverage_dictionary[key] = coverage[0]
2
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artbio
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diff changeset
203 self.write_table(coverage_dictionary, out)
0
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204
2
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artbio
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diff changeset
205 def compute_size(self, map_dictionary, out):
0
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artbio
parents:
diff changeset
206 '''
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artbio
parents:
diff changeset
207 Takes a map_dictionary and returns a dictionary of sizes:
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artbio
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208 {chrom: {polarity: {size: nbre of reads}}}
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artbio
parents:
diff changeset
209 '''
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artbio
parents:
diff changeset
210 size_dictionary = defaultdict(lambda: defaultdict(
1
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artbio
parents: 0
diff changeset
211 lambda: defaultdict(int)))
0
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artbio
parents:
diff changeset
212 # to track empty chromosomes
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artbio
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213 for chrom in self.chromosomes:
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artbio
parents:
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214 if self.bam_object.count(chrom) == 0:
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artbio
parents:
diff changeset
215 size_dictionary[chrom]['F'][10] = 0
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artbio
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diff changeset
216 for key in map_dictionary:
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artbio
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217 for size in map_dictionary[key]:
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artbio
parents:
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218 size_dictionary[key[0]][key[2]][size] += 1
2
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artbio
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diff changeset
219 self.write_size_table(size_dictionary, out)
0
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artbio
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220
2
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artbio
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diff changeset
221 def write_table(self, mapdict, out):
0
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artbio
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222 '''
2
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artbio
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diff changeset
223 Generic writer
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artbio
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diff changeset
224 Dataset, Chromosome, Chrom_length, Coordinate, Polarity,
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artbio
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diff changeset
225 <some mapped value>
0
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artbio
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diff changeset
226 out is an *open* file handler
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artbio
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227 '''
2
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diff changeset
228 for key in sorted(mapdict):
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229 line = [self.sample_name, key[0], self.chromosomes[key[0]],
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diff changeset
230 key[1], key[2], mapdict[key]]
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artbio
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diff changeset
231 line = [str(i) for i in line]
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diff changeset
232 out.write('\t'.join(line) + '\n')
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artbio
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diff changeset
233
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diff changeset
234 def write_size_table(self, sizedic, out):
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diff changeset
235 '''
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artbio
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diff changeset
236 Generic writer of summary values
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artbio
parents: 1
diff changeset
237 Dataset, Chromosome, Chrom_length, <some category>, <some value>
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artbio
parents: 1
diff changeset
238 out is an *open* file handler
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artbio
parents: 1
diff changeset
239 '''
507383cce5a8 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit edbb53cb13b52bf8e71c562fa8acc2c3be2fb270
artbio
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diff changeset
240 for chrom in sorted(sizedic):
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artbio
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diff changeset
241 sizes = sizedic[chrom]['F'].keys()
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artbio
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diff changeset
242 sizes.extend(sizedic[chrom]['R'].keys())
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artbio
parents: 1
diff changeset
243 for polarity in sorted(sizedic[chrom]):
0
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artbio
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diff changeset
244 for size in range(min(sizes), max(sizes)+1):
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artbio
parents:
diff changeset
245 try:
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artbio
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diff changeset
246 line = [self.sample_name, chrom, polarity, size,
2
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artbio
parents: 1
diff changeset
247 sizedic[chrom][polarity][size]]
0
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artbio
parents:
diff changeset
248 except KeyError:
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artbio
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diff changeset
249 line = [self.sample_name, chrom, polarity, size, 0]
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artbio
parents:
diff changeset
250 line = [str(i) for i in line]
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artbio
parents:
diff changeset
251 out.write('\t'.join(line) + '\n')
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artbio
parents:
diff changeset
252
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artbio
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diff changeset
253
9
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artbio
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diff changeset
254 def main(inputs, samples, methods, outputs, minsize, maxsize, cluster):
2
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artbio
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diff changeset
255 for method, output in zip(methods, outputs):
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artbio
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diff changeset
256 F = open(output, 'w')
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artbio
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257 if method == 'Size':
5
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artbio
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diff changeset
258 header = ["Dataset", "Chromosome", "Polarity", method, "Counts"]
2
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artbio
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diff changeset
259 else:
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diff changeset
260 header = ["Dataset", "Chromosome", "Chrom_length", "Coordinate",
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artbio
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diff changeset
261 "Polarity", method]
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artbio
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diff changeset
262 F.write('\t'.join(header) + '\n')
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diff changeset
263 for input, sample in zip(inputs, samples):
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264 mapobj = Map(input, sample, minsize, maxsize, cluster)
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265 token = {"Counts": mapobj.compute_readcount,
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266 "Max": mapobj.compute_max,
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267 "Mean": mapobj.compute_mean,
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268 "Median": mapobj.compute_median,
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269 "Coverage": mapobj.compute_coverage,
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270 "Size": mapobj.compute_size}
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271 token[method](mapobj.map_dict, F)
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272 F.close()
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273
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274
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275 if __name__ == "__main__":
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276 args = Parser()
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277 # if identical sample names
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278 if len(set(args.sample_names)) != len(args.sample_names):
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279 args.sample_names = [name + '_' + str(i) for
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280 i, name in enumerate(args.sample_names)]
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281 main(args.inputs, args.sample_names, args.plot_methods, args.outputs,
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282 args.minsize, args.maxsize, args.cluster)