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0
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1 import argparse
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2 import os
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3 import pandas
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4 import pypandoc
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5 import re
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6 import subprocess
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7 import sys
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8
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9 from Bio import SeqIO
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10 from datetime import date
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11 from mdutils.mdutils import MdUtils
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12
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13 CDC_ADVISORY = 'The analysis and report presented here should be treated as preliminary. Please contact the CDC/BDRD with any results regarding _Bacillus anthracis_.'
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14
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15
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16 class PimaReport:
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17
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1
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18 def __init__(self, analysis_name=None, amr_deletions_file=None, amr_matrix_files=None, assembly_fasta_file=None,
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19 assembly_name=None, compute_sequence_length_file=None, contig_coverage_file=None, dbkey=None,
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20 dnadiff_snps_file=None, feature_bed_files=None, feature_png_files=None, flye_assembly_info_file=None,
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21 flye_version=None, genome_insertions_file=None, gzipped=None, illumina_fastq_file=None,
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22 mutation_regions_bed_file=None, mutation_regions_tsv_files=None, pima_css=None, plasmids_file=None,
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23 reference_insertions_file=None):
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0
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24 self.ofh = open("process_log.txt", "w")
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25
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1
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26 self.ofh.write("amr_deletions_file: %s\n" % str(amr_deletions_file))
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27 self.ofh.write("amr_matrix_files: %s\n" % str(amr_matrix_files))
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28 self.ofh.write("analysis_name: %s\n" % str(analysis_name))
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29 self.ofh.write("assembly_fasta_file: %s\n" % str(assembly_fasta_file))
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30 self.ofh.write("assembly_name: %s\n" % str(assembly_name))
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1
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31 self.ofh.write("compute_sequence_length_file: %s\n" % str(compute_sequence_length_file))
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32 self.ofh.write("contig_coverage_file: %s\n" % str(contig_coverage_file))
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33 self.ofh.write("dbkey: %s\n" % str(dbkey))
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34 self.ofh.write("dnadiff_snps_file: %s\n" % str(dnadiff_snps_file))
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35 self.ofh.write("feature_bed_files: %s\n" % str(feature_bed_files))
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36 self.ofh.write("feature_png_files: %s\n" % str(feature_png_files))
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1
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37 self.ofh.write("flye_assembly_info_file: %s\n" % str(flye_assembly_info_file))
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38 self.ofh.write("flye_version: %s\n" % str(flye_version))
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39 self.ofh.write("gzipped: %s\n" % str(gzipped))
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1
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40 self.ofh.write("genome_insertions_file: %s\n" % str(genome_insertions_file))
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41 self.ofh.write("illumina_fastq_file: %s\n" % str(illumina_fastq_file))
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42 self.ofh.write("mutation_regions_bed_file: %s\n" % str(mutation_regions_bed_file))
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43 self.ofh.write("mutation_regions_tsv_files: %s\n" % str(mutation_regions_tsv_files))
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44 self.ofh.write("pima_css: %s\n" % str(pima_css))
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1
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45 self.ofh.write("plasmids_file: %s\n" % str(plasmids_file))
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46 # self.ofh.write("reference_genome: %s\n" % str(reference_genome))
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47 self.ofh.write("reference_insertions_file: %s\n" % str(reference_insertions_file))
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48
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49 # General
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50 self.doc = None
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51 self.report_md = 'pima_report.md'
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52
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53 # Inputs
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1
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54 self.amr_deletions_file = amr_deletions_file
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55 self.amr_matrix_files = amr_matrix_files
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0
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56 self.analysis_name = analysis_name
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57 self.assembly_fasta_file = assembly_fasta_file
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58 self.assembly_name = assembly_name
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1
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59 self.compute_sequence_length_file = compute_sequence_length_file
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60 self.contig_coverage_file = contig_coverage_file
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61 self.dbkey = dbkey
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62 self.dnadiff_snps_file = dnadiff_snps_file
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63 self.feature_bed_files = feature_bed_files
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64 self.feature_png_files = feature_png_files
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1
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65 self.flye_assembly_info_file = flye_assembly_info_file
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66 self.flye_version = flye_version
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67 self.gzipped = gzipped
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68 self.genome_insertions_file = genome_insertions_file
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69 self.illumina_fastq_file = illumina_fastq_file
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70 self.mutation_regions_bed_file = mutation_regions_bed_file
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71 self.mutation_regions_tsv_files = mutation_regions_tsv_files
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72 self.read_type = 'Illumina'
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73 self.ont_bases = None
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74 self.ont_n50 = None
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75 self.ont_read_count = None
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76 self.pima_css = pima_css
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1
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77 self.plasmids_file = plasmids_file
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78 # self.reference_genome = reference_genome
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79 self.reference_insertions_file = reference_insertions_file
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80
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81 # Titles
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82 self.alignment_title = 'Comparison with reference'
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83 self.alignment_notes_title = 'Alignment notes'
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84 self.amr_matrix_title = 'AMR matrix'
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85 self.assembly_methods_title = 'Assembly'
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86 self.assembly_notes_title = 'Assembly notes'
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87 self.basecalling_title = 'Basecalling'
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88 self.basecalling_methods_title = 'Basecalling'
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89 self.contamination_methods_title = 'Contamination check'
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90 self.contig_alignment_title = 'Alignment vs. reference contigs'
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91 self.feature_title = 'Features found in the assembly'
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92 self.feature_methods_title = 'Feature annotation'
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93 self.feature_plot_title = 'Feature annotation plots'
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94 self.large_indel_title = 'Large insertions & deletions'
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95 self.methods_title = 'Methods'
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96 self.mutation_title = 'Mutations found in the sample'
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97 self.mutation_methods_title = 'Mutation screening'
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98 self.plasmid_methods_title = 'Plasmid annotation'
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1
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99 self.plasmid_title = 'Plasmid annotation'
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100 self.reference_methods_title = 'Reference comparison'
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101 self.snp_indel_title = 'SNPs and small indels'
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102 self.summary_title = 'Analysis of %s' % analysis_name
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103
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104 # Methods
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105 self.methods = pandas.Series(dtype='float64')
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106 self.methods[self.contamination_methods_title] = pandas.Series(dtype='float64')
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107 self.methods[self.assembly_methods_title] = pandas.Series(dtype='float64')
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108 self.methods[self.reference_methods_title] = pandas.Series(dtype='float64')
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109 self.methods[self.mutation_methods_title] = pandas.Series(dtype='float64')
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110 self.methods[self.feature_methods_title] = pandas.Series(dtype='float64')
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111 self.methods[self.plasmid_methods_title] = pandas.Series(dtype='float64')
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112
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113 # Contamination
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114 self.kraken_fracs = pandas.Series(dtype=object)
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115
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116 # Notes
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117 self.assembly_notes = pandas.Series(dtype=object)
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118 self.alignment_notes = pandas.Series(dtype=object)
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119 self.contig_alignment = pandas.Series(dtype=object)
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120
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121 # Values
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122 self.assembly_size = 0
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123 self.contig_info = None
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124 self.did_medaka_ont_assembly = False
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125 self.feature_hits = pandas.Series(dtype='float64')
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126 self.illumina_length_mean = 0
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127 self.illumina_read_count = 0
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128 self.illumina_bases = 0
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129 self.mean_coverage = 0
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130 self.num_assembly_contigs = 0
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1
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131 # TODO: should the following 2 values be passed as parameters?
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132 self.ont_n50_min = 2500
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133 self.ont_coverage_min = 30
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134 self.quast_indels = 0
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135 self.quast_mismatches = 0
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0
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136
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137 # Actions
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138 self.did_guppy_ont_fast5 = False
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139 self.did_qcat_ont_fastq = False
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140 self.info_illumina_fastq()
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141 self.load_contig_info()
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142
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143 def run_command(self, command):
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144 self.ofh.write("\nXXXXXX In run_command, command:\n%s\n\n" % str(command))
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145 try:
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146 return re.split('\\n', subprocess.check_output(command, shell=True).decode('utf-8'))
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147 except Exception:
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148 message = 'Command %s failed: exiting...' % command
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149 sys.exit(message)
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150
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151 def format_kmg(self, number, decimals=0):
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152 self.ofh.write("\nXXXXXX In format_kmg, number:\n%s\n" % str(number))
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153 self.ofh.write("XXXXXX In format_kmg, decimals:\n%s\n\n" % str(decimals))
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154 if number == 0:
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155 return '0'
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156 magnitude_powers = [10**9, 10**6, 10**3, 1]
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157 magnitude_units = ['G', 'M', 'K', '']
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158 for i in range(len(magnitude_units)):
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159 if number >= magnitude_powers[i]:
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160 magnitude_power = magnitude_powers[i]
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161 magnitude_unit = magnitude_units[i]
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162 return ('{:0.' + str(decimals) + 'f}').format(number / magnitude_power) + magnitude_unit
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163
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164 def load_contig_info(self):
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165 self.contig_info = pandas.Series(dtype=object)
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166 self.contig_info[self.read_type] = pandas.read_csv(self.contig_coverage_file, header=None, index_col=None, sep='\t').sort_values(1, axis=0, ascending=False)
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167 self.contig_info[self.read_type].columns = ['contig', 'size', 'coverage']
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168 self.mean_coverage = (self.contig_info[self.read_type].iloc[:, 1] * self.contig_info[self.read_type].iloc[:, 2]).sum() / self.contig_info[self.read_type].iloc[:, 1].sum()
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169 if self.mean_coverage <= self.ont_coverage_min:
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170 warning = '%s mean coverage ({:.0f}X) is less than the recommended minimum ({:.0f}X).'.format(self.mean_coverage, self.ont_coverage_min) % self.read_type
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171 self.assembly_notes = self.assembly_notes.append(pandas.Series(warning))
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172 # Report if some contigs have low coverage.
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173 low_coverage = self.contig_info[self.read_type].loc[self.contig_info[self.read_type]['coverage'] < self.ont_coverage_min, :]
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174 if low_coverage.shape[0] >= 0:
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175 for contig_i in range(low_coverage.shape[0]):
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176 warning = '%s coverage of {:s} ({:.0f}X) is less than the recommended minimum ({:.0f}X).'.format(low_coverage.iloc[contig_i, 0], low_coverage.iloc[contig_i, 2], self.ont_coverage_min) % self.read_type
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177 self.assembly_notes = self.assembly_notes.append(pandas.Series(warning))
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178 # See if some contigs have anolously low coverage.
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179 fold_coverage = self.contig_info[self.read_type]['coverage'] / self.mean_coverage
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180 low_coverage = self.contig_info[self.read_type].loc[fold_coverage < 1 / 5, :]
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181 if low_coverage.shape[0] >= 0 :
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182 for contig_i in range(low_coverage.shape[0]):
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183 warning = '%s coverage of {:s} ({:.0f}X) is less than 1/5 the mean coverage ({:.0f}X).'.format(low_coverage.iloc[contig_i, 0], low_coverage.iloc[contig_i, 2], self.mean_coverage) % self.read_type
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184 self.assembly_notes = self.assembly_notes.append(pandas.Series(warning))
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0
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185
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186 def load_fasta(self, fasta):
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187 sequence = pandas.Series(dtype=object)
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188 for contig in SeqIO.parse(fasta, 'fasta'):
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189 sequence[contig.id] = contig
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190 return sequence
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191
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192 def load_assembly(self):
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193 self.assembly = self.load_fasta(self.assembly_fasta_file)
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194 self.num_assembly_contigs = len(self.assembly)
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195 for i in self.assembly:
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196 self.assembly_size += len(i.seq)
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197 self.assembly_size = self.format_kmg(self.assembly_size, decimals=1)
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198
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199 def info_illumina_fastq(self):
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200 self.ofh.write("\nXXXXXX In info_illumina_fastq\n\n")
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201 if self.gzipped:
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202 opener = 'gunzip -c'
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203 else:
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204 opener = 'cat'
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205 command = ' '.join([opener,
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206 self.illumina_fastq_file,
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207 '| awk \'{getline;s += length($1);getline;getline;}END{print s/(NR/4)"\t"(NR/4)"\t"s}\''])
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208 output = self.run_command(command)
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209 self.ofh.write("output:\n%s\n" % str(output))
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210 self.ofh.write("re.split('\\t', self.run_command(command)[0]:\n%s\n" % str(re.split('\\t', self.run_command(command)[0])))
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211 values = []
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212 for i in re.split('\\t', self.run_command(command)[0]):
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213 if i == '':
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214 values.append(float('nan'))
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215 else:
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216 values.append(float(i))
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217 self.ofh.write("values:\n%s\n" % str(values))
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218 self.ofh.write("values[0]:\n%s\n" % str(values[0]))
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219 self.illumina_length_mean += values[0]
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220 self.ofh.write("values[1]:\n%s\n" % str(values[1]))
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221 self.illumina_read_count += int(values[1])
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222 self.ofh.write("values[2]:\n%s\n" % str(values[2]))
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223 self.illumina_bases += int(values[2])
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224 # The original PIMA code inserts self.illumina_fastq into
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225 # a list for no apparent reason. We don't do that here.
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226 # self.illumina_length_mean /= len(self.illumina_fastq)
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227 self.illumina_length_mean /= 1
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228 self.illumina_bases = self.format_kmg(self.illumina_bases, decimals=1)
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229
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230 def start_doc(self):
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231 self.doc = MdUtils(file_name=self.report_md, title='')
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232
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233 def add_run_information(self):
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234 self.ofh.write("\nXXXXXX In add_run_information\n\n")
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235 self.doc.new_line()
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236 self.doc.new_header(1, 'Run information')
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237 # Tables in md.utils are implemented as a wrapping function.
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238 Table_list = [
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239 "Category",
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240 "Information",
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241 "Date",
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242 date.today(),
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243 "ONT FAST5",
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244 "N/A",
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245 "ONT FASTQ",
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246 "N/A",
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247 "Illumina FASTQ",
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248 self.wordwrap_markdown(self.analysis_name),
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249 "Assembly",
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250 self.wordwrap_markdown(self.assembly_name),
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251 "Reference",
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252 self.wordwrap_markdown(self.dbkey),
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253 ]
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254 self.doc.new_table(columns=2, rows=7, text=Table_list, text_align='left')
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255 self.doc.new_line()
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256 self.doc.new_line()
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257
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258 def add_ont_library_information(self):
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259 self.ofh.write("\nXXXXXX In add_ont_library_information\n\n")
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260 if self.ont_n50 is None:
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261 return
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262 self.doc.new_line()
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263 self.doc.new_header(2, 'ONT library statistics')
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264 Table_List = [
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265 "Category",
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266 "Quantity",
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267 "ONT N50",
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268 '{:,}'.format(self.ont_n50),
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269 "ONT reads",
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270 '{:,}'.format(self.ont_read_count),
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271 "ONT bases",
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272 '{:s}'.format(self.ont_bases),
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273 "Illumina FASTQ",
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274 self.wordwrap_markdown(self.illumina_fastq_file),
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275 "Assembly",
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276 self.wordwrap_markdown(self.assembly_name),
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277 "Reference",
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278 self.wordwrap_markdown(self.dbkey),
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279 ]
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280 self.doc.new_table(columns=2, rows=7, text=Table_List, text_align='left')
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281 self.doc.new_line()
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282
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283 def add_illumina_library_information(self):
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284 self.ofh.write("\nXXXXXX In add_illumina_library_information\n\n")
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285 if self.illumina_length_mean is None:
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286 return
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287 self.doc.new_line()
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288 self.doc.new_header(2, 'Illumina library statistics')
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289 Table_List = [
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290 "Illumina Info.",
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291 "Quantity",
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292 'Illumina mean length',
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293 '{:.1f}'.format(self.illumina_length_mean),
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294 'Illumina reads',
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295 '{:,}'.format(self.illumina_read_count),
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296 'Illumina bases',
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297 '{:s}'.format(self.illumina_bases)
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298 ]
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299 self.doc.new_table(columns=2, rows=4, text=Table_List, text_align='left')
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300
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1
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301 def evaluate_assembly(self) :
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302 assembly_info = pandas.read_csv(self.compute_sequence_length_file, sep='\t', header=None)
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303 assembly_info.columns = ['contig', 'length']
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304 self.contig_sizes = assembly_info
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305 # Take a look at the number of contigs, their sizes,
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306 # and circularity. Warn if things don't look good.
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307 if assembly_info.shape[0] > 4:
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308 warning = 'Assembly produced {:d} contigs, more than ususally expected; assembly may be fragmented'.format(assembly_info.shape[0])
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309 self.assembly_notes = self.assembly_notes.append(pandas.Series(warning))
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310 small_contigs = assembly_info.loc[assembly_info['length'] <= 3000, :]
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311 if small_contigs.shape[0] > 0:
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312 warning = 'Assembly produced {:d} small contigs ({:s}); assembly may include spurious sequences.'.format(small_contigs.shape[0], ', '.join(small_contigs['contig']))
|
|
|
313 self.assembly_notes = self.assembly_notes.append(pandas.Series(warning))
|
|
|
314
|
|
0
|
315 def add_assembly_information(self):
|
|
|
316 self.ofh.write("\nXXXXXX In add_assembly_information\n\n")
|
|
|
317 if self.assembly_fasta_file is None:
|
|
|
318 return
|
|
|
319 self.load_assembly()
|
|
|
320 self.doc.new_line()
|
|
|
321 self.doc.new_header(2, 'Assembly statistics')
|
|
|
322 Table_List = [
|
|
|
323 "Category",
|
|
|
324 "Information",
|
|
|
325 "Contigs",
|
|
|
326 str(self.num_assembly_contigs),
|
|
|
327 "Assembly size",
|
|
|
328 str(self.assembly_size),
|
|
|
329 ]
|
|
|
330 self.doc.new_table(columns=2, rows=3, text=Table_List, text_align='left')
|
|
|
331
|
|
|
332 def info_ont_fastq(self, fastq_file):
|
|
|
333 self.ofh.write("\nXXXXXX In info_ont_fastq, fastq_file:\n%s\n\n" % str(fastq_file))
|
|
|
334 opener = 'cat'
|
|
|
335 if self.gzipped:
|
|
|
336 opener = 'gunzip -c'
|
|
|
337 else:
|
|
|
338 opener = 'cat'
|
|
|
339 command = ' '.join([opener,
|
|
|
340 fastq_file,
|
|
|
341 '| awk \'{getline;print length($0);s += length($1);getline;getline;}END{print "+"s}\'',
|
|
|
342 '| sort -gr',
|
|
|
343 '| awk \'BEGIN{bp = 0;f = 0}',
|
|
|
344 '{if(NR == 1){sub(/+/, "", $1);s=$1}else{bp += $1;if(bp > s / 2 && f == 0){n50 = $1;f = 1}}}',
|
|
|
345 'END{printf "%d\\t%d\\t%d\\n", n50, (NR - 1), s;exit}\''])
|
|
|
346 result = list(re.split('\\t', self.run_command(command)[0]))
|
|
|
347 if result[1] == '0':
|
|
|
348 self.error_out('No ONT reads found')
|
|
|
349 ont_n50, ont_read_count, ont_raw_bases = [int(i) for i in result]
|
|
|
350 command = ' '.join([opener,
|
|
|
351 fastq_file,
|
|
|
352 '| awk \'{getline;print length($0);getline;getline;}\''])
|
|
|
353 result = self.run_command(command)
|
|
|
354 result = list(filter(lambda x: x != '', result))
|
|
1
|
355 # TODO: the following are not yet used...
|
|
|
356 # ont_read_lengths = [int(i) for i in result]
|
|
|
357 # ont_bases = self.format_kmg(ont_raw_bases, decimals=1)
|
|
|
358 if ont_n50 <= self.ont_n50_min:
|
|
|
359 warning = 'ONT N50 (%s) is less than the recommended minimum (%s)' % (str(ont_n50), str(self.ont_n50_min))
|
|
|
360 self.assembly_notes = self.assembly_notes.append(pandas.Series(warning))
|
|
0
|
361
|
|
|
362 def wordwrap_markdown(self, string):
|
|
|
363 if string:
|
|
|
364 if len(string) < 35:
|
|
|
365 return string
|
|
|
366 else:
|
|
|
367 if '/' in string:
|
|
|
368 adjust = string.split('/')
|
|
|
369 out = ''
|
|
|
370 max = 35
|
|
|
371 for i in adjust:
|
|
|
372 out = out + '/' + i
|
|
|
373 if len(out) > max:
|
|
|
374 out += '<br>'
|
|
|
375 max += 35
|
|
|
376 return out
|
|
|
377 else:
|
|
|
378 out = [string[i:i + 35] for i in range(0, len(string), 50)]
|
|
|
379 return '<br>'.join(out)
|
|
|
380 else:
|
|
|
381 return string
|
|
|
382
|
|
|
383 def add_contig_info(self):
|
|
|
384 self.ofh.write("\nXXXXXX In add_contig_info\n\n")
|
|
|
385 if self.contig_info is None:
|
|
|
386 return
|
|
|
387 for method in ['ONT', 'Illumina']:
|
|
|
388 if method not in self.contig_info.index:
|
|
|
389 continue
|
|
|
390 self.doc.new_line()
|
|
|
391 self.doc.new_header(2, 'Assembly coverage by ' + method)
|
|
|
392 Table_List = ["Contig", "Length (bp)", "Coverage (X)"]
|
|
|
393 formatted = self.contig_info[method].copy()
|
|
|
394 formatted.iloc[:, 1] = formatted.iloc[:, 1].apply(lambda x: '{:,}'.format(x))
|
|
|
395 for i in range(self.contig_info[method].shape[0]):
|
|
|
396 Table_List = Table_List + formatted.iloc[i, :].values.tolist()
|
|
|
397 row_count = int(len(Table_List) / 3)
|
|
|
398 self.doc.new_table(columns=3, rows=row_count, text=Table_List, text_align='left')
|
|
|
399
|
|
|
400 def add_assembly_notes(self):
|
|
|
401 self.ofh.write("\nXXXXXX In add_assembly_notes\n\n")
|
|
|
402 if len(self.assembly_notes) == 0:
|
|
|
403 return
|
|
|
404 self.doc.new_line()
|
|
|
405 self.doc.new_line('<div style="page-break-after: always;"></div>')
|
|
|
406 self.doc.new_line()
|
|
|
407 self.doc.new_header(2, self.assembly_notes_title)
|
|
1
|
408 for note in self.assembly_notes:
|
|
|
409 self.doc.new_line(note)
|
|
0
|
410
|
|
|
411 def add_contamination(self):
|
|
|
412 self.ofh.write("\nXXXXXX In add_contamination\n\n")
|
|
|
413 if len(self.kraken_fracs) == 0:
|
|
|
414 return
|
|
|
415 self.doc.new_line()
|
|
|
416 self.doc.new_header(2, 'Contamination check')
|
|
|
417 for read_type, kraken_fracs in self.kraken_fracs.iteritems():
|
|
|
418 self.doc.new_line(read_type + ' classifications')
|
|
|
419 self.doc.new_line()
|
|
|
420 Table_List = ["Percent of Reads", "Reads", "Level", "Label"]
|
|
|
421 for index, row in kraken_fracs.iterrows():
|
|
|
422 Table_List = Table_List + row.tolist()
|
|
|
423 row_count = int(len(Table_List) / 4)
|
|
|
424 self.doc.new_table(columns=4, rows=row_count, text=Table_List, text_align='left')
|
|
|
425 if self.contamination_methods_title not in self.methods:
|
|
|
426 self.methods[self.contamination_methods_title] = ''
|
|
|
427 method = 'Kraken2 was used to assign the raw reads into taxa.'
|
|
|
428 self.methods[self.contamination_methods_title] = self.methods[self.contamination_methods_title].append(pandas.Series(method))
|
|
|
429
|
|
|
430 def add_alignment(self):
|
|
|
431 self.ofh.write("\nXXXXXX In add_alignment\n\n")
|
|
|
432 # TODO: implement the draw_circos function for this.
|
|
|
433 if len(self.contig_alignment) > 0:
|
|
|
434 alignments = self.contig_alignment
|
|
|
435 else:
|
|
|
436 return
|
|
|
437 self.doc.new_line()
|
|
|
438 self.doc.new_header(level=2, title=self.alignment_title)
|
|
|
439 self.doc.new_line()
|
|
|
440 self.doc.new_header(level=3, title=self.snp_indel_title)
|
|
|
441 Table_1 = [
|
|
|
442 "Category",
|
|
|
443 "Quantity",
|
|
|
444 'SNPs',
|
|
1
|
445 '{:,}'.format(self.quast_mismatches),
|
|
0
|
446 'Small indels',
|
|
1
|
447 '{:,}'.format(self.quast_indels)
|
|
0
|
448 ]
|
|
|
449 self.doc.new_table(columns=2, rows=3, text=Table_1, text_align='left')
|
|
|
450 self.doc.new_line('<div style="page-break-after: always;"></div>')
|
|
|
451 self.doc.new_line()
|
|
|
452 if len(self.alignment_notes) > 0:
|
|
|
453 self.doc.new_header(level=3, title=self.alignment_notes_title)
|
|
|
454 for note in self.alignment_notes:
|
|
|
455 self.doc.new_line(note)
|
|
|
456 for contig in alignments.index.tolist():
|
|
|
457 contig_title = 'Alignment to %s' % contig
|
|
|
458 image_png = alignments[contig]
|
|
|
459 self.doc.new_line()
|
|
|
460 self.doc.new_header(level=3, title=contig_title)
|
|
|
461 self.doc.new_line(self.doc.new_inline_image(text='contig_title', path=os.path.abspath(image_png)))
|
|
|
462 self.doc.new_line('<div style="page-break-after: always;"></div>')
|
|
|
463 self.doc.new_line()
|
|
|
464 method = 'The genome assembly was aligned against the reference sequencing using dnadiff.'
|
|
|
465 self.methods[self.reference_methods_title] = self.methods[self.reference_methods_title].append(pandas.Series(method))
|
|
|
466
|
|
|
467 def add_features(self):
|
|
|
468 self.ofh.write("\nXXXXXX In add_features\n\n")
|
|
|
469 if len(self.feature_bed_files) == 0:
|
|
|
470 return
|
|
|
471 for bbf in self.feature_bed_files:
|
|
|
472 if os.path.getsize(bbf) > 0:
|
|
|
473 best = pandas.read_csv(filepath_or_buffer=bbf, sep='\t', header=None)
|
|
|
474 self.feature_hits[os.path.basename(bbf)] = best
|
|
|
475 if len(self.feature_hits) == 0:
|
|
|
476 return
|
|
|
477 self.ofh.write("self.feature_hits: %s\n" % str(self.feature_hits))
|
|
|
478 self.doc.new_line()
|
|
|
479 self.doc.new_header(level=2, title=self.feature_title)
|
|
|
480 for feature_name in self.feature_hits.index.tolist():
|
|
|
481 self.ofh.write("feature_name: %s\n" % str(feature_name))
|
|
|
482 features = self.feature_hits[feature_name].copy()
|
|
|
483 self.ofh.write("features: %s\n" % str(features))
|
|
|
484 if features.shape[0] == 0:
|
|
|
485 continue
|
|
|
486 features.iloc[:, 1] = features.iloc[:, 1].apply(lambda x: '{:,}'.format(x))
|
|
|
487 features.iloc[:, 2] = features.iloc[:, 2].apply(lambda x: '{:,}'.format(x))
|
|
|
488 self.doc.new_line()
|
|
|
489 self.doc.new_header(level=3, title=feature_name)
|
|
|
490 if (features.shape[0] == 0):
|
|
|
491 continue
|
|
|
492 for contig in pandas.unique(features.iloc[:, 0]):
|
|
|
493 self.ofh.write("contig: %s\n" % str(contig))
|
|
|
494 self.doc.new_line(contig)
|
|
|
495 contig_features = features.loc[(features.iloc[:, 0] == contig), :]
|
|
|
496 self.ofh.write("contig_features: %s\n" % str(contig_features))
|
|
|
497 Table_List = ['Start', 'Stop', 'Feature', 'Identity (%)', 'Strand']
|
|
|
498 for i in range(contig_features.shape[0]):
|
|
|
499 self.ofh.write("i: %s\n" % str(i))
|
|
|
500 feature = contig_features.iloc[i, :].copy(deep=True)
|
|
|
501 self.ofh.write("feature: %s\n" % str(feature))
|
|
|
502 feature[4] = '{:.3f}'.format(feature[4])
|
|
1
|
503 # FIXME: Uncommenting the following line (which is
|
|
|
504 # https://github.com/appliedbinf/pima_md/blob/main/MarkdownReport.py#L317)
|
|
|
505 # will cause the job to fail with this exception:
|
|
|
506 # ValueError: columns * rows is not equal to text length
|
|
|
507 # Table_List = Table_List + feature[1:].values.tolist()
|
|
0
|
508 self.ofh.write("Table_List: %s\n" % str(Table_List))
|
|
|
509 row_count = int(len(Table_List) / 5)
|
|
|
510 self.ofh.write("row_count: %s\n" % str(row_count))
|
|
|
511 self.doc.new_line()
|
|
1
|
512 self.ofh.write("Before new_table, len(Table_List):: %s\n" % str(len(Table_List)))
|
|
|
513 self.doc.new_table(columns=5, rows=row_count, text=Table_List, text_align='left')
|
|
0
|
514 blastn_version = 'The genome assembly was queried for features using blastn.'
|
|
|
515 bedtools_version = 'Feature hits were clustered using bedtools and the highest scoring hit for each cluster was reported.'
|
|
|
516 method = '%s %s' % (blastn_version, bedtools_version)
|
|
|
517 self.methods[self.feature_methods_title] = self.methods[self.feature_methods_title].append(pandas.Series(method))
|
|
|
518
|
|
|
519 def add_feature_plots(self):
|
|
|
520 self.ofh.write("\nXXXXXX In add_feature_plots\n\n")
|
|
|
521 if len(self.feature_png_files) == 0:
|
|
|
522 return
|
|
|
523 self.doc.new_line()
|
|
|
524 self.doc.new_header(level=2, title='Feature Plots')
|
|
|
525 self.doc.new_paragraph('Only contigs with features are shown')
|
|
|
526 for feature_png_file in self.feature_png_files:
|
|
|
527 self.doc.new_line(self.doc.new_inline_image(text='Analysis', path=os.path.abspath(feature_png_file)))
|
|
|
528
|
|
|
529 def add_mutations(self):
|
|
|
530 self.ofh.write("\nXXXXXX In add_mutations\n\n")
|
|
|
531 if len(self.mutation_regions_tsv_files) == 0:
|
|
|
532 return
|
|
1
|
533 try :
|
|
0
|
534 mutation_regions = pandas.read_csv(self.mutation_regions_bed_file, sep='\t', header=0, index_col=False)
|
|
|
535 except Exception:
|
|
|
536 # Likely an empty file.
|
|
|
537 return
|
|
1
|
538 # TODO: this is the only place where reference_genome is used,
|
|
|
539 # so I'm commenting it out for now. We need to confirm if these
|
|
|
540 # errors that require the reference genmoe being passed are necessary.
|
|
|
541 # If so, we'll need to implement data tables in this tool.
|
|
|
542 # Make sure that the positions in the BED file fall within
|
|
|
543 # the chromosomes provided in the reference sequence.
|
|
|
544 """
|
|
|
545 for mutation_region in range(mutation_regions.shape[0]):
|
|
|
546 mutation_region = mutation_regions.iloc[mutation_region, :]
|
|
|
547 if not (mutation_region[0] in self.reference_genome):
|
|
|
548 self.ofh.write("\nMutation region: %s not found in reference genome.\n" % ' '.join(mutation_region.astype(str)))
|
|
|
549 continue
|
|
|
550 if not isinstance(mutation_region[1], int):
|
|
|
551 self.ofh.write("\nNon-integer found in mutation region start (column 2): %s.\n" % str(mutation_region[1]))
|
|
|
552 break
|
|
|
553 elif not isinstance(mutation_region[2], int):
|
|
|
554 self.ofh.write("\nNon-integer found in mutation region start (column 3): %s.\n" % str(mutation_region[2]))
|
|
|
555 break
|
|
|
556 if mutation_region[1] <= 0 or mutation_region[2] <= 0:
|
|
|
557 self.ofh.write("\nMutation region %s starts before the reference sequence.\n" % ' '.join(mutation_region.astype(str)))
|
|
|
558 if mutation_region[1] > len(self.reference_genome[mutation_region[0]].seq) or mutation_region[2] > len(self.reference_genome[mutation_region[0]].seq):
|
|
|
559 self.ofh.write("\nMutation region %s ends after the reference sequence.\n" % ' '.join(mutation_region.astype(str)))
|
|
|
560 """
|
|
0
|
561 amr_mutations = pandas.Series(dtype=object)
|
|
|
562 for region_i in range(mutation_regions.shape[0]):
|
|
|
563 region = mutation_regions.iloc[region_i, :]
|
|
|
564 region_name = str(region['name'])
|
|
|
565 self.ofh.write("Processing mutations for region %s\n" % region_name)
|
|
|
566 region_mutations_tsv_name = '%s_mutations.tsv' % region_name
|
|
|
567 if region_mutations_tsv_name not in self.mutation_regions_tsv_files:
|
|
|
568 continue
|
|
|
569 region_mutations_tsv = self.mutation_regions_tsv_files[region_mutations_tsv_name]
|
|
1
|
570 try :
|
|
0
|
571 region_mutations = pandas.read_csv(region_mutations_tsv, sep='\t', header=0, index_col=False)
|
|
|
572 except Exception:
|
|
|
573 region_mutations = pandas.DataFrame()
|
|
|
574 if region_mutations.shape[0] == 0:
|
|
|
575 continue
|
|
1
|
576 # Figure out what kind of mutations are in this region.
|
|
0
|
577 region_mutation_types = pandas.Series(['snp'] * region_mutations.shape[0], name='TYPE', index=region_mutations.index)
|
|
|
578 region_mutation_types[region_mutations['REF'].str.len() != region_mutations['ALT'].str.len()] = 'small-indel'
|
|
|
579 region_mutation_drugs = pandas.Series(region['drug'] * region_mutations.shape[0], name='DRUG', index=region_mutations.index)
|
|
|
580 region_notes = pandas.Series(region['note'] * region_mutations.shape[0], name='NOTE', index=region_mutations.index)
|
|
|
581 region_mutations = pandas.concat([region_mutations, region_mutation_types, region_mutation_drugs, region_notes], axis=1)
|
|
|
582 region_mutations = region_mutations[['#CHROM', 'POS', 'TYPE', 'REF', 'ALT', 'DRUG', 'NOTE']]
|
|
|
583 amr_mutations[region['name']] = region_mutations
|
|
|
584 # Report the mutations.
|
|
|
585 self.doc.new_line()
|
|
|
586 self.doc.new_header(level=2, title=self.mutation_title)
|
|
|
587 for region_name in amr_mutations.index.tolist():
|
|
|
588 region_mutations = amr_mutations[region_name].copy()
|
|
|
589 self.doc.new_line()
|
|
|
590 self.doc.new_header(level=3, title=region_name)
|
|
|
591 if (region_mutations.shape[0] == 0):
|
|
|
592 self.doc.append('None')
|
|
|
593 continue
|
|
|
594 region_mutations.iloc[:, 1] = region_mutations.iloc[:, 1].apply(lambda x: '{:,}'.format(x))
|
|
|
595 Table_List = ['Reference contig', 'Position', 'Reference', 'Alternate', 'Drug', 'Note']
|
|
|
596 for i in range(region_mutations.shape[0]):
|
|
|
597 Table_List = Table_List + region_mutations.iloc[i, [0, 1, 3, 4, 5, 6]].values.tolist()
|
|
|
598 row_count = int(len(Table_List) / 6)
|
|
|
599 self.doc.new_table(columns=6, rows=row_count, text=Table_List, text_align='left')
|
|
|
600 method = '%s reads were mapped to the reference sequence using minimap2.' % self.read_type
|
|
|
601 self.methods[self.mutation_methods_title] = self.methods[self.mutation_methods_title].append(pandas.Series(method))
|
|
|
602 method = 'Mutations were identified using samtools mpileup and varscan.'
|
|
|
603 self.methods[self.mutation_methods_title] = self.methods[self.mutation_methods_title].append(pandas.Series(method))
|
|
|
604
|
|
|
605 def add_amr_matrix(self):
|
|
|
606 self.ofh.write("\nXXXXXX In add_amr_matrix\n\n")
|
|
|
607 # Make sure that we have an AMR matrix to plot
|
|
1
|
608 if len(self.amr_matrix_files) == 0:
|
|
|
609 return
|
|
|
610 self.doc.new_line()
|
|
|
611 self.doc.new_header(level=2, title=self.amr_matrix_title)
|
|
|
612 self.doc.new_line('AMR genes and mutations with their corresponding drugs')
|
|
|
613 for amr_matrix_file in self.amr_matrix_files:
|
|
|
614 self.doc.new_line(self.doc.new_inline_image(text='AMR genes and mutations with their corresponding drugs',
|
|
|
615 path=os.path.abspath(amr_matrix_file)))
|
|
0
|
616
|
|
|
617 def add_large_indels(self):
|
|
|
618 self.ofh.write("\nXXXXXX In add_large_indels\n\n")
|
|
1
|
619 large_indels = pandas.Series(dtype='float64')
|
|
|
620 # Pull in insertions.
|
|
|
621 try:
|
|
|
622 reference_insertions = pandas.read_csv(filepath_or_buffer=self.reference_insertions_file, sep='\t', header=None)
|
|
|
623 except Exception:
|
|
|
624 reference_insertions = pandas.DataFrame()
|
|
|
625 try:
|
|
|
626 genome_insertions = pandas.read_csv(filepath_or_buffer=self.genome_insertions_file, sep='\t', header=None)
|
|
|
627 except Exception:
|
|
|
628 genome_insertions = pandas.DataFrame()
|
|
|
629 large_indels['Reference insertions'] = reference_insertions
|
|
|
630 large_indels['Query insertions'] = genome_insertions
|
|
|
631 # TODO: we don't seem to be reporting snps and deletions for some reason...
|
|
|
632 # Pull in the number of SNPs and small indels.
|
|
|
633 try:
|
|
|
634 snps = pandas.read_csv(filepath_or_buffer=self.dnadiff_snps_file, sep='\t', header=None)
|
|
|
635 # TODO: the following is not used...
|
|
|
636 # small_indels = snps.loc[(snps.iloc[:, 1] == '.') | (snps.iloc[:, 2] == '.'), :]
|
|
|
637 snps = snps.loc[(snps.iloc[:, 1] != '.') & (snps.iloc[:, 2] != '.'), :]
|
|
|
638 except Exception:
|
|
|
639 snps = pandas.DataFrame()
|
|
|
640 # Pull in deletions.
|
|
|
641 try:
|
|
|
642 amr_deletions = pandas.read_csv(filepath_or_buffer=self.amr_deletion_file, sep='\t', header=None)
|
|
|
643 except Exception:
|
|
|
644 amr_deletions = pandas.DataFrame()
|
|
|
645 if amr_deletions.shape[0] > 0:
|
|
|
646 amr_deletions.columns = ['contig', 'start', 'stop', 'name', 'type', 'drug', 'note']
|
|
|
647 amr_deletions = amr_deletions.loc[amr_deletions['type'].isin(['large-deletion', 'any']), :]
|
|
|
648 self.doc.new_line()
|
|
|
649 self.doc.new_header(level=2, title=self.large_indel_title)
|
|
|
650 for genome in ['Reference insertions', 'Query insertions']:
|
|
|
651 genome_indels = large_indels[genome].copy()
|
|
|
652 self.doc.new_line()
|
|
|
653 self.doc.new_header(level=3, title=genome)
|
|
|
654 if (genome_indels.shape[0] == 0):
|
|
|
655 continue
|
|
|
656 genome_indels.iloc[:, 1] = genome_indels.iloc[:, 1].apply(lambda x: '{:,}'.format(x))
|
|
|
657 genome_indels.iloc[:, 2] = genome_indels.iloc[:, 2].apply(lambda x: '{:,}'.format(x))
|
|
|
658 genome_indels.iloc[:, 3] = genome_indels.iloc[:, 3].apply(lambda x: '{:,}'.format(x))
|
|
|
659 Table_List = [
|
|
|
660 'Reference contig', 'Start', 'Stop', 'Size (bp)'
|
|
|
661 ]
|
|
|
662 for i in range(genome_indels.shape[0]):
|
|
|
663 Table_List = Table_List + genome_indels.iloc[i, :].values.tolist()
|
|
|
664 row_count = int(len(Table_List) / 4)
|
|
|
665 self.doc.new_table(columns=4, rows=row_count, text=Table_List, text_align='left')
|
|
|
666 method = 'Large insertions or deletions were found as the complement of aligned regions using bedtools.'
|
|
|
667 self.methods[self.reference_methods_title] = self.methods[self.reference_methods_title].append(pandas.Series(method))
|
|
|
668 self.doc.new_line()
|
|
|
669 self.doc.new_line('<div style="page-break-after: always;"></div>')
|
|
|
670 self.doc.new_line()
|
|
0
|
671
|
|
|
672 def add_plasmids(self):
|
|
1
|
673 try :
|
|
|
674 plasmids = pandas.read_csv(filepath_or_buffer=self.plasmids_file, sep='\t', header=0)
|
|
|
675 except Exception:
|
|
0
|
676 return
|
|
|
677 plasmids = plasmids.copy()
|
|
|
678 self.doc.new_line()
|
|
1
|
679 self.doc.new_header(level=2, title=self.plasmid_title)
|
|
0
|
680 if (plasmids.shape[0] == 0):
|
|
|
681 self.doc.new_line('None')
|
|
|
682 return
|
|
|
683 plasmids.iloc[:, 3] = plasmids.iloc[:, 3].apply(lambda x: '{:,}'.format(x))
|
|
|
684 plasmids.iloc[:, 4] = plasmids.iloc[:, 4].apply(lambda x: '{:,}'.format(x))
|
|
|
685 plasmids.iloc[:, 5] = plasmids.iloc[:, 5].apply(lambda x: '{:,}'.format(x))
|
|
1
|
686 Table_List = ['Genome contig', 'Plasmid hit', 'Plasmid acc.', 'Contig size', 'Aliged', 'Plasmid size']
|
|
0
|
687 for i in range(plasmids.shape[0]):
|
|
|
688 Table_List = Table_List + plasmids.iloc[i, 0:6].values.tolist()
|
|
|
689 row_count = int(len(Table_List) / 6)
|
|
|
690 self.doc.new_table(columns=6, rows=row_count, text=Table_List, text_align='left')
|
|
|
691 method = 'The plasmid reference database was queried against the genome assembly using minimap2.'
|
|
|
692 self.methods[self.plasmid_methods_title] = self.methods[self.plasmid_methods_title].append(pandas.Series(method))
|
|
|
693 method = 'The resulting SAM was converted to a PSL using a custom version of sam2psl.'
|
|
|
694 self.methods[self.plasmid_methods_title] = self.methods[self.plasmid_methods_title].append(pandas.Series(method))
|
|
|
695 method = 'Plasmid-to-genome hits were resolved using the pChunks algorithm.'
|
|
|
696 self.methods[self.plasmid_methods_title] = self.methods[self.plasmid_methods_title].append(pandas.Series(method))
|
|
|
697
|
|
|
698 def add_methods(self):
|
|
|
699 self.ofh.write("\nXXXXXX In add_methods\n\n")
|
|
|
700 self.doc.new_line('<div style="page-break-after: always;"></div>')
|
|
|
701 self.doc.new_line()
|
|
|
702 if len(self.methods) == 0:
|
|
|
703 return
|
|
|
704 self.doc.new_line()
|
|
|
705 self.doc.new_header(level=2, title=self.methods_title)
|
|
|
706 for methods_section in self.methods.index.tolist():
|
|
|
707 if self.methods[methods_section] is None or len(self.methods[methods_section]) == 0:
|
|
|
708 continue
|
|
|
709 self.doc.new_line()
|
|
|
710 self.doc.new_header(level=3, title=methods_section)
|
|
|
711 self.doc.new_paragraph(' '.join(self.methods[methods_section]))
|
|
|
712
|
|
|
713 def add_summary(self):
|
|
|
714 self.ofh.write("\nXXXXXX In add_summary\n\n")
|
|
|
715 # Add summary title
|
|
|
716 self.doc.new_header(level=1, title=self.summary_title)
|
|
|
717 # First section of Summary
|
|
|
718 self.doc.new_header(level=1, title='CDC Advisory')
|
|
|
719 self.doc.new_paragraph(CDC_ADVISORY)
|
|
|
720 self.doc.new_line()
|
|
|
721 self.add_run_information()
|
|
|
722 self.add_ont_library_information()
|
|
|
723 methods = []
|
|
|
724 if self.did_guppy_ont_fast5:
|
|
|
725 methods += ['ONT reads were basecalled using guppy']
|
|
|
726 if self.did_qcat_ont_fastq:
|
|
|
727 methods += ['ONT reads were demultiplexed and trimmed using qcat']
|
|
|
728 self.methods[self.basecalling_methods_title] = pandas.Series(methods)
|
|
|
729 self.add_illumina_library_information()
|
|
1
|
730 self.add_contig_info()
|
|
|
731 self.evaluate_assembly()
|
|
0
|
732 self.add_assembly_information()
|
|
1
|
733 if self.flye_assembly_info_file is not None:
|
|
|
734 method = 'ONT reads were assembled using %s' % self.flye_version
|
|
0
|
735 self.methods[self.assembly_methods_title] = self.methods[self.assembly_methods_title].append(pandas.Series(method))
|
|
1
|
736 # Pull in the assembly summary and look at the coverage.
|
|
|
737 assembly_info = pandas.read_csv(self.flye_assembly_info_file, header=0, index_col=0, sep='\t')
|
|
|
738 # Look for non-circular contigs.
|
|
|
739 open_contigs = assembly_info.loc[assembly_info['circ.'] == 'N', :]
|
|
|
740 if open_contigs.shape[0] > 0:
|
|
|
741 open_contig_ids = open_contigs.index.values
|
|
|
742 warning = 'Flye reported {:d} open contigs ({:s}); assembly may be incomplete.'.format(open_contigs.shape[0], ', '.join(open_contig_ids))
|
|
|
743 self.assembly_notes = self.assembly_notes.append(pandas.Series(warning))
|
|
0
|
744 if self.did_medaka_ont_assembly:
|
|
|
745 method = 'the genome assembly was polished using ont reads and medaka.'
|
|
|
746 self.methods[self.assembly_methods_title] = self.methods[self.assembly_methods_title].append(pandas.series(method))
|
|
1
|
747 self.info_ont_fastq(self.illumina_fastq_file)
|
|
|
748 self.add_assembly_notes()
|
|
0
|
749
|
|
|
750 def make_tex(self):
|
|
|
751 self.doc.new_table_of_contents(table_title='detailed run information', depth=2, marker="tableofcontents")
|
|
|
752 text = self.doc.file_data_text
|
|
|
753 text = text.replace("##--[", "")
|
|
|
754 text = text.replace("]--##", "")
|
|
|
755 self.doc.file_data_text = text
|
|
|
756 self.doc.create_md_file()
|
|
|
757
|
|
|
758 def make_report(self):
|
|
|
759 self.ofh.write("\nXXXXXX In make_report\n\n")
|
|
|
760 self.start_doc()
|
|
|
761 self.add_summary()
|
|
|
762 self.add_contamination()
|
|
|
763 self.add_alignment()
|
|
|
764 self.add_features()
|
|
|
765 self.add_feature_plots()
|
|
|
766 self.add_mutations()
|
|
|
767 self.add_large_indels()
|
|
|
768 self.add_plasmids()
|
|
1
|
769 # TODO stuff working to here...
|
|
0
|
770 self.add_amr_matrix()
|
|
|
771 # self.add_snps()
|
|
|
772 self.add_methods()
|
|
|
773 self.make_tex()
|
|
|
774 # It took me quite a long time to find out that the value of the -t
|
|
|
775 # (implied) argument in the following command must be 'html' instead of
|
|
|
776 # the more logical 'pdf'. see the answer from snsn in this thread:
|
|
|
777 # https://github.com/jessicategner/pypandoc/issues/186
|
|
|
778 self.ofh.write("\nXXXXX In make_report, calling pypandoc.convert_file...\n\n")
|
|
|
779 pypandoc.convert_file(self.report_md,
|
|
|
780 'html',
|
|
|
781 extra_args=['--pdf-engine=weasyprint', '-V', '-css=%s' % self.pima_css],
|
|
|
782 outputfile='pima_report.pdf')
|
|
|
783 self.ofh.close()
|
|
|
784
|
|
|
785
|
|
|
786 parser = argparse.ArgumentParser()
|
|
|
787
|
|
1
|
788 parser.add_argument('--amr_deletions_file', action='store', dest='amr_deletions_file', help='AMR deletions BED file')
|
|
|
789 parser.add_argument('--amr_matrix_png_dir', action='store', dest='amr_matrix_png_dir', help='Directory of AMR matrix PNG files')
|
|
0
|
790 parser.add_argument('--analysis_name', action='store', dest='analysis_name', help='Sample identifier')
|
|
|
791 parser.add_argument('--assembly_fasta_file', action='store', dest='assembly_fasta_file', help='Assembly fasta file')
|
|
|
792 parser.add_argument('--assembly_name', action='store', dest='assembly_name', help='Assembly identifier')
|
|
1
|
793 parser.add_argument('--compute_sequence_length_file', action='store', dest='compute_sequence_length_file', help='Comnpute sequence length tabular file')
|
|
|
794 parser.add_argument('--contig_coverage_file', action='store', dest='contig_coverage_file', help='Contig coverage TSV file')
|
|
|
795 parser.add_argument('--dbkey', action='store', dest='dbkey', help='Reference genome identifier')
|
|
|
796 parser.add_argument('--dnadiff_snps_file', action='store', dest='dnadiff_snps_file', help='DNAdiff snps tabular file')
|
|
0
|
797 parser.add_argument('--feature_bed_dir', action='store', dest='feature_bed_dir', help='Directory of best feature hits bed files')
|
|
|
798 parser.add_argument('--feature_png_dir', action='store', dest='feature_png_dir', help='Directory of best feature hits png files')
|
|
1
|
799 parser.add_argument('--flye_assembly_info_file', action='store', dest='flye_assembly_info_file', default=None, help='Flye assembly info tabular file')
|
|
|
800 parser.add_argument('--flye_version', action='store', dest='flye_version', default=None, help='Flye version string')
|
|
|
801 parser.add_argument('--genome_insertions_file', action='store', dest='genome_insertions_file', help='Genome insertions BED file')
|
|
0
|
802 parser.add_argument('--gzipped', action='store_true', dest='gzipped', default=False, help='Input sample is gzipped')
|
|
|
803 parser.add_argument('--illumina_fastq_file', action='store', dest='illumina_fastq_file', help='Input sample')
|
|
|
804 parser.add_argument('--mutation_regions_bed_file', action='store', dest='mutation_regions_bed_file', help='AMR mutation regions BRD file')
|
|
|
805 parser.add_argument('--mutation_regions_dir', action='store', dest='mutation_regions_dir', help='Directory of mutation regions TSV files')
|
|
|
806 parser.add_argument('--pima_css', action='store', dest='pima_css', help='PIMA css stypesheet')
|
|
1
|
807 parser.add_argument('--plasmids_file', action='store', dest='plasmids_file', help='pChunks plasmids TSV file')
|
|
|
808 parser.add_argument('--reference_insertions_file', action='store', dest='reference_insertions_file', help='Reference insertions BED file')
|
|
|
809 # parser.add_argument('--reference_genome', action='store', dest='reference_genome', help='Reference genome fasta file')
|
|
0
|
810
|
|
|
811 args = parser.parse_args()
|
|
|
812
|
|
1
|
813 # Prepare the AMR matrix PNG files.
|
|
|
814 amr_matrix_files = []
|
|
|
815 for file_name in sorted(os.listdir(args.amr_matrix_png_dir)):
|
|
|
816 file_path = os.path.abspath(os.path.join(args.amr_matrix_png_dir, file_name))
|
|
|
817 amr_matrix_files.append(file_path)
|
|
0
|
818 # Prepare the features BED files.
|
|
|
819 feature_bed_files = []
|
|
|
820 for file_name in sorted(os.listdir(args.feature_bed_dir)):
|
|
|
821 file_path = os.path.abspath(os.path.join(args.feature_bed_dir, file_name))
|
|
|
822 feature_bed_files.append(file_path)
|
|
|
823 # Prepare the features PNG files.
|
|
|
824 feature_png_files = []
|
|
|
825 for file_name in sorted(os.listdir(args.feature_png_dir)):
|
|
|
826 file_path = os.path.abspath(os.path.join(args.feature_png_dir, file_name))
|
|
|
827 feature_png_files.append(file_path)
|
|
|
828 # Prepare the mutation regions TSV files.
|
|
|
829 mutation_regions_files = []
|
|
|
830 for file_name in sorted(os.listdir(args.mutation_regions_dir)):
|
|
|
831 file_path = os.path.abspath(os.path.join(args.feature_png_dir, file_name))
|
|
|
832 mutation_regions_files.append(file_path)
|
|
|
833
|
|
|
834 markdown_report = PimaReport(args.analysis_name,
|
|
1
|
835 args.amr_deletions_file,
|
|
|
836 amr_matrix_files,
|
|
0
|
837 args.assembly_fasta_file,
|
|
|
838 args.assembly_name,
|
|
1
|
839 args.compute_sequence_length_file,
|
|
|
840 args.contig_coverage_file,
|
|
|
841 args.dbkey,
|
|
|
842 args.dnadiff_snps_file,
|
|
0
|
843 feature_bed_files,
|
|
|
844 feature_png_files,
|
|
1
|
845 args.flye_assembly_info_file,
|
|
|
846 args.flye_version,
|
|
|
847 args.genome_insertions_file,
|
|
0
|
848 args.gzipped,
|
|
|
849 args.illumina_fastq_file,
|
|
|
850 args.mutation_regions_bed_file,
|
|
|
851 mutation_regions_files,
|
|
1
|
852 args.pima_css,
|
|
|
853 args.plasmids_file,
|
|
|
854 args.reference_insertions_file)
|
|
0
|
855 markdown_report.make_report()
|
