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1 #!/usr/bin/env python
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2
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3 import argparse
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4 import csv
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5 import os
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4
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6 import subprocess
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7 import sys
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8 import tempfile
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9
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10 import Bio.SeqIO
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11 import numpy
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12 import pandas
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13 import matplotlib.pyplot as pyplot
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14
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15
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1
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16 def get_amr_in_feature_hits(amr_feature_hits):
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17 for k in amr_feature_hits.keys():
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18 if k.lower().find('amr') >= 0:
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19 return amr_feature_hits[k]
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20 return None
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21
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22
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4
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23 def load_fasta(fasta_file):
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24 sequence = pandas.Series(dtype=object)
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25 for contig in Bio.SeqIO.parse(fasta_file, 'fasta'):
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26 sequence[contig.id] = contig
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27 return sequence
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28
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29
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30 def run_command(cmd):
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31 try:
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32 tmp_name = tempfile.NamedTemporaryFile(dir=".").name
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33 tmp_stderr = open(tmp_name, 'wb')
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34 proc = subprocess.Popen(args=cmd, shell=True, stderr=tmp_stderr.fileno())
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35 returncode = proc.wait()
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36 tmp_stderr.close()
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37 if returncode != 0:
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38 # Get stderr, allowing for case where it's very large.
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39 tmp_stderr = open(tmp_name, 'rb')
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40 stderr = ''
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41 buffsize = 1048576
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42 try:
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43 while True:
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44 stderr += tmp_stderr.read(buffsize)
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45 if not stderr or len(stderr) % buffsize != 0:
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46 break
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47 except OverflowError:
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48 pass
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49 tmp_stderr.close()
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50 os.remove(tmp_name)
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51 stop_err(stderr)
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52 except Exception as e:
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53 stop_err('Command:\n%s\n\nended with error:\n%s\n\n' % (cmd, str(e)))
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54
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55
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56 def stop_err(msg):
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57 sys.stderr.write(msg)
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58 sys.exit(1)
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59
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60
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15
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61 def draw_amr_matrix(amr_feature_hits_files, amr_deletions_file, varscan_vcf_file, amr_mutation_regions_bed_file, amr_gene_drug_file, reference, reference_size, mutation_regions_dir, amr_matrix_png_dir, errors):
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62 efh = open(errors, 'w')
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63 ofh = open('process_log', 'w')
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64
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65 # Read amr_feature_hits_files.
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66 amr_feature_hits = pandas.Series(dtype=object)
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67 for amr_feature_hits_file in amr_feature_hits_files:
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68 ofh.write("\namr_feature_hits_file: %s\n" % amr_feature_hits_file)
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69 feature_name = os.path.basename(amr_feature_hits_file)
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70 ofh.write("\nfeature_name: %s\n" % feature_name)
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71 # Make sure the file is not empty.
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72 if os.path.isfile(amr_feature_hits_file) and os.path.getsize(amr_feature_hits_file) > 0:
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73 best_hits = pandas.read_csv(filepath_or_buffer=amr_feature_hits_file, sep='\t', header=None)
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74 ofh.write("\nFeature file %s will be processed\n" % os.path.basename(amr_feature_hits_file))
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75 else:
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76 ofh.write("\nEmpty feature file %s will NOT be processed\n" % os.path.basename(amr_feature_hits_file))
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77 best_hits = None
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78 amr_feature_hits[feature_name] = best_hits
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79
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80 amr_hits = get_amr_in_feature_hits(amr_feature_hits)
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81 ofh.write("\namr_hits:\n%s\n" % str(amr_hits))
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82 if amr_hits is not None:
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83 amr_to_draw = pandas.DataFrame(columns=['gene', 'drug'])
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84 ofh.write("\namr_to_draw:\n%s\n" % str(amr_to_draw))
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85 # Read amr_drug_gene_file.
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86 amr_gene_drug = pandas.read_csv(amr_gene_drug_file, index_col=None, sep='\t', quoting=csv.QUOTE_NONE, header=None)
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87 ofh.write("\namr_gene_drug:\n%s\n" % str(amr_gene_drug))
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88
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89 # Roll up AMR gene hits.
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90 ofh.write("\namr_hits.shape[0]: %s\n" % str(amr_hits.shape[0]))
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91 if amr_hits.shape[0] > 0:
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92 for gene_idx, gene in amr_hits.iterrows():
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93 ofh.write("gene_idx: %s\n" % str(gene_idx))
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94 ofh.write("gene: %s\n" % str(gene))
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95 gene_name = gene[3]
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96 ofh.write("gene_name: %s\n" % str(gene_name))
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97 ofh.write("amr_gene_drug[0]: %s\n" % str(amr_gene_drug[0]))
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98 drugs = amr_gene_drug.loc[amr_gene_drug[0] == gene_name, :][1]
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99 ofh.write("drugs: %s\n" % str(drugs))
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100 for drug in drugs:
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101 amr_to_draw = amr_to_draw.append(pandas.Series([gene_name, drug], name=amr_to_draw.shape[0], index=amr_to_draw.columns))
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102 ofh.write("\amr_to_draw: %s\n" % str(amr_to_draw))
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103
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104 ofh.write("\nvarscan_vcf_file is None: %s\n" % str(varscan_vcf_file == 'None'))
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105 if varscan_vcf_file not in [None, 'None'] and os.path.getsize(varscan_vcf_file) > 0:
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106 amr_mutations = pandas.Series(dtype=object)
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107 if amr_mutation_regions_bed_file is not None:
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108 mutation_regions = pandas.read_csv(amr_mutation_regions_bed_file, header=0, sep='\t', index_col=False)
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109 # Validate mutation regions.
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110 if mutation_regions.shape[1] != 7:
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111 efh.write("The selected mutations regions BED file is invalid, it should be a six column file.\n")
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112 elif mutation_regions.shape[0] == 0:
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113 efh.write("There are no rows in the selected mutation regions file.\n")
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114 else:
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115 for region_i in range(mutation_regions.shape[0]):
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116 region = mutation_regions.iloc[region_i, :]
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117 if region[0] not in reference:
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118 efh.write("Mutation region '%s' not found in reference genome.\n" % str(region))
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119 break
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120 if not isinstance(region[1], numpy.int64):
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121 efh.write("Non-integer found in mutation region start (column 2): %s.\n" % str(region[1]))
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122 break
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123 if not isinstance(region[2], numpy.int64):
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124 efh.write("Non-integer found in mutation region start (column 3): %s.\n" % str(region[2]))
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125 break
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126 if region[1] <= 0 or region[2] <= 0:
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127 efh.write("Mutation region '%s' starts before the reference sequence.\n" % str(region))
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128 if region[1] > len(reference[region[0]].seq) or region[2] > len(reference[region[0]].seq):
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129 efh.write("Mutation region '%s' ends after the reference sequence.\n" % str(region))
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130 if not region.get('type', default='No Type') in ['snp', 'small-indel', 'any']:
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131 ofh.write("\n\nSkipping mutation region '%s' with invalid type '%s', valid types are 'snp', 'small-indel', 'any'.\n\n" % (str(region), str(region.get('type', default='No Type'))))
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132 continue
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133 ofh.write("\nFinding AMR mutations for %s.\n" % str(region['name']))
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134 region_bed = 'region_%s.bed' % region_i
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135 ofh.write("region_bed: %s\n" % str(region_bed))
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136 mutation_regions.loc[[region_i], ].to_csv(path_or_buf=region_bed, sep='\t', header=False, index=False)
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137 ofh.write("mutation_regions.loc[[region_i], ]:\n%s\n" % str(mutation_regions.loc[[region_i], ]))
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138 region_mutations_tsv = os.path.join(mutation_regions_dir, 'region_%s_mutations.tsv' % region_i)
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139 ofh.write("region_mutations_tsv: %s\n" % str(region_mutations_tsv))
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140 cmd = ' '.join(['bedtools intersect',
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141 '-nonamecheck',
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142 '-wb',
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143 '-a', region_bed,
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144 '-b', varscan_vcf_file,
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145 ' | awk \'BEGIN{getline < "' + amr_mutation_regions_bed_file + '";printf $0"\\t";',
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146 'getline < "' + varscan_vcf_file + '"; getline < "' + varscan_vcf_file + '";print $0}{print}\'',
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147 '1>' + region_mutations_tsv])
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148 ofh.write("\ncmd:\n%s\n" % cmd)
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149 run_command(cmd)
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150 try:
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151 ofh.write("After running command, os.path.getsize((region_mutations_tsv): %s\n" % str(os.path.getsize(region_mutations_tsv)))
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152 region_mutations = pandas.read_csv(region_mutations_tsv, sep='\t', header=0, index_col=False)
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153 ofh.write("\nregion_mutations: %s\n" % region_mutations)
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154 except Exception:
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155 continue
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156 # Figure out what kind of mutations are in this region.
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157 region_mutation_types = pandas.Series(['snp'] * region_mutations.shape[0], name='TYPE', index=region_mutations.index)
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158 region_mutation_types[region_mutations['REF'].str.len() != region_mutations['ALT'].str.len()] = 'small-indel'
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159 region_mutation_drugs = pandas.Series(region['drug'] * region_mutations.shape[0], name='DRUG', index=region_mutations.index)
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160 region_notes = pandas.Series(region['note'] * region_mutations.shape[0], name='NOTE', index=region_mutations.index)
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161 region_mutations = pandas.concat([region_mutations, region_mutation_types, region_mutation_drugs, region_notes], axis=1)
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162 region_mutations = region_mutations[['#CHROM', 'POS', 'TYPE', 'REF', 'ALT', 'DRUG', 'NOTE']]
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163 amr_mutations[region['name']] = region_mutations
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164 else:
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165 ofh.write("\nMutation region BED file not received.\n")
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166 ofh.write("\nAfter processing mutations, amr_mutations: %s\n" % str(amr_mutations))
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167 # Roll up potentially resistance conferring mutations.
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168 ofh.write("\n##### Rolling up potentially resistance conferring mutations..\n")
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169 for mutation_region, mutation_hits in amr_mutations.iteritems():
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170 ofh.write("mutation_region: %s\n" % str(mutation_region))
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171 ofh.write("mutation_hits: %s\n" % str(mutation_hits))
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172 for mutation_idx, mutation_hit in mutation_hits.iterrows():
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173 ofh.write("mutation_idx: %s\n" % str(mutation_idx))
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174 ofh.write("mutation_hit: %s\n" % str(mutation_hit))
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175 mutation_name = mutation_region + ' ' + mutation_hit['REF'] + '->' + mutation_hit['ALT']
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176 ofh.write("mutation_name: %s\n" % str(mutation_name))
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177 amr_to_draw = amr_to_draw.append(pandas.Series([mutation_name, mutation_hit['DRUG']], name=amr_to_draw.shape[0], index=amr_to_draw.columns))
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178 ofh.write("\nAfter processing mutations, amr_to_draw: %s\n" % str(amr_to_draw))
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179 ofh.write("\nAfter processing mutations, amr_to_draw.shape[0]: %s\n" % str(amr_to_draw.shape[0]))
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180
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181 if amr_deletions_file not in [None, 'None'] and os.path.getsize(amr_deletions_file) > 0:
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182 # Roll up deletions that might confer resistance.
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183 try:
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184 amr_deletions = pandas.read_csv(filepath_or_buffer=amr_deletions_file, sep='\t', header=None)
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185 except Exception:
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186 amr_deletions = pandas.DataFrame()
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187 if amr_deletions.shape[0] > 0:
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188 amr_deletions.columns = ['contig', 'start', 'stop', 'name', 'type', 'drug', 'note']
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189 amr_deletions = amr_deletions.loc[amr_deletions['type'].isin(['large-deletion', 'any']), :]
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190 for deletion_idx, deleted_gene in amr_deletions.iterrows():
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191 amr_to_draw = amr_to_draw.append(pandas.Series(['\u0394' + deleted_gene[3], deleted_gene[5]], name=amr_to_draw.shape[0], index=amr_to_draw.columns))
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192 ofh.write("\nAfter processing deletions, amr_to_draw: %s\n" % str(amr_to_draw))
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193
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194 ofh.write("\namr_to_draw.shape[0]: %s\n" % str(amr_to_draw.shape[0]))
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195 # I have no idea why, but when running functional tests with planemo
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196 # the value of amr_to_draw.shape[0] is 1 even though the tests use the
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197 # exact inputs when running outside of planeo that result in the value
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198 # being 2. So we cannot test with planemo unless we incorporate a hack
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199 # like a hidden in_test_mode parameter.
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200 if amr_to_draw.shape[0] > 1:
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201 ofh.write("\nDrawing AMR matrix...\n")
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202 present_genes = amr_to_draw['gene'].unique()
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203 present_drugs = amr_to_draw['drug'].unique()
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204 amr_matrix = pandas.DataFrame(0, index=present_genes, columns=present_drugs)
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205 for hit_idx, hit in amr_to_draw.iterrows():
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206 amr_matrix.loc[hit[0], hit[1]] = 1
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207 amr_matrix_png = os.path.join(amr_matrix_png_dir, 'amr_matrix.png')
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208 int_matrix = amr_matrix[amr_matrix.columns].astype(int)
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209 figure, axis = pyplot.subplots()
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210 heatmap = axis.pcolor(int_matrix, cmap=pyplot.cm.Blues, linewidth=0)
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211 axis.invert_yaxis()
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212 axis.set_yticks(numpy.arange(0.5, len(amr_matrix.index)), minor=False)
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213 axis.set_yticklabels(int_matrix.index.values)
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214 axis.set_xticks(numpy.arange(0.5, len(amr_matrix.columns)), minor=False)
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215 axis.set_xticklabels(amr_matrix.columns.values, rotation=90)
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216 axis.xaxis.tick_top()
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217 axis.xaxis.set_label_position('top')
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218 pyplot.tight_layout()
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219 pyplot.savefig(amr_matrix_png, dpi=300)
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220 else:
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221 ofh.write("\nEmpty AMR matrix, nothing to draw...\n")
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222 efh.close()
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223 ofh.close()
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224
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225
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226 if __name__ == '__main__':
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227 parser = argparse.ArgumentParser()
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228
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229 parser.add_argument('--amr_feature_hits_dir', action='store', dest='amr_feature_hits_dir', help='Directory of tabular files containing feature hits')
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230 parser.add_argument('--amr_deletions_file', action='store', dest='amr_deletions_file', default=None, help='AMR deletions BED file')
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231 parser.add_argument('--varscan_vcf_file', action='store', dest='varscan_vcf_file', default=None, help='Varscan VCF file produced by the call_amr_mutations tool')
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232 parser.add_argument('--amr_mutation_regions_bed_file', action='store', dest='amr_mutation_regions_bed_file', default=None, help='AMR mutation regions BED file')
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233 parser.add_argument('--amr_gene_drug_file', action='store', dest='amr_gene_drug_file', help='AMR_gene_drugs tsv file')
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234 parser.add_argument('--reference_genome', action='store', dest='reference_genome', help='Reference genome fasta file')
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235 parser.add_argument('--mutation_regions_dir', action='store', dest='mutation_regions_dir', help='Directory for mutation regions TSV files produced by this tool')
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236 parser.add_argument('--amr_matrix_png_dir', action='store', dest='amr_matrix_png_dir', help='Directory for PNG files produced by this tool')
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237 parser.add_argument('--errors', action='store', dest='errors', help='Output file containing errors')
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238
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239 args = parser.parse_args()
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240
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241 # Get the collection of feature hits files. The collection
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242 # will be sorted alphabetically and will contain 2 files
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243 # named something like AMR_CDS_311_2022_12_20.fasta and
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244 # Incompatibility_Groups_2023_01_01.fasta.
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245 amr_feature_hits_files = []
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246 for file_name in sorted(os.listdir(args.amr_feature_hits_dir)):
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247 file_path = os.path.abspath(os.path.join(args.amr_feature_hits_dir, file_name))
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248 amr_feature_hits_files.append(file_path)
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249
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250 # Load the reference genome into memory.
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251 reference = load_fasta(args.reference_genome)
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252 reference_size = 0
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253 for i in reference:
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254 reference_size += len(i.seq)
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255
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256 draw_amr_matrix(amr_feature_hits_files, args.amr_deletions_file, args.varscan_vcf_file, args.amr_mutation_regions_bed_file, args.amr_gene_drug_file, reference, reference_size, args.mutation_regions_dir, args.amr_matrix_png_dir, args.errors)
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