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