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1 """
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2 A module originally obtained from the cravat package. Modified to use in the vcf
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3 converter galaxy tool.
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4
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5
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6 Register of changes made (Chris Jacoby):
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7 1) Changed imports as galaxy tool won't have access to complete cravat python package
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8 2) Defined BadFormatError in BaseConverted file, as I didn't have the BadFormatError module
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9 """
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10
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11 from base_converter import BaseConverter, BadFormatError
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12 import re
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13
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14 class CravatConverter(BaseConverter):
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15
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16 def __init__(self):
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17 self.format_name = 'vcf'
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18 self.samples = []
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19 self.var_counter = 0
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20 self.addl_cols = [{'name':'phred',
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21 'title':'Phred',
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22 'type':'string'},
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23 {'name':'filter',
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24 'title':'VCF filter',
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25 'type':'string'},
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26 {'name':'zygosity',
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27 'title':'Zygosity',
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28 'type':'string'},
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29 {'name':'alt_reads',
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30 'title':'Alternate reads',
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31 'type':'int'},
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32 {'name':'tot_reads',
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33 'title':'Total reads',
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34 'type':'int'},
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35 {'name':'af',
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36 'title':'Variant allele frequency',
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37 'type':'float'}]
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38
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39 def check_format(self, f):
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40 return f.readline().startswith('##fileformat=VCF')
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41
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42 def setup(self, f):
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43
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44 vcf_line_no = 0
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45 for line in f:
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46 vcf_line_no += 1
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47 if len(line) < 6:
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48 continue
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49 if line[:6] == '#CHROM':
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50 toks = re.split('\s+', line.rstrip())
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51 if len(toks) > 8:
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52 self.samples = toks[9:]
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53 break
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54
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55 def convert_line(self, l):
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56 if l.startswith('#'): return None
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57 self.var_counter += 1
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58 toks = l.strip('\r\n').split('\t')
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59 all_wdicts = []
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60 if len(toks) < 8:
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61 raise BadFormatError('Wrong VCF format')
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62 [chrom, pos, tag, ref, alts, qual, filter, info] = toks[:8]
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63 if tag == '':
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64 raise BadFormatError('ID column is blank')
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65 elif tag == '.':
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66 tag = 'VAR' + str(self.var_counter)
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67 if chrom[:3] != 'chr':
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68 chrom = 'chr' + chrom
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69 alts = alts.split(',')
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70 len_alts = len(alts)
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71 if len(toks) == 8:
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72 for altno in range(len_alts):
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73 wdict = None
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74 alt = alts[altno]
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75 newpos, newref, newalt = self.extract_vcf_variant('+', pos, ref, alt)
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76 wdict = {'tags':tag,
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77 'chrom':chrom,
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78 'pos':newpos,
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79 'ref_base':newref,
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80 'alt_base':newalt,
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81 'sample_id':'no_sample',
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82 'phred': qual,
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83 'filter': filter}
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84 all_wdicts.append(wdict)
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85 elif len(toks) > 8:
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86 sample_datas = toks[9:]
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87 genotype_fields = {}
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88 genotype_field_no = 0
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89 for genotype_field in toks[8].split(':'):
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90 genotype_fields[genotype_field] = genotype_field_no
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91 genotype_field_no += 1
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92 if not ('GT' in genotype_fields):
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93 raise BadFormatError('No GT Field')
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94 gt_field_no = genotype_fields['GT']
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95 for sample_no in range(len(sample_datas)):
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96 sample = self.samples[sample_no]
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97 sample_data = sample_datas[sample_no].split(':')
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98 gts = {}
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99 for gt in sample_data[gt_field_no].replace('/', '|').split('|'):
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100 if gt == '.':
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101 continue
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102 else:
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103 gts[int(gt)] = True
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104 for gt in sorted(gts.keys()):
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105 wdict = None
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106 if gt == 0:
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107 continue
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108 else:
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109 alt = alts[gt - 1]
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110 newpos, newref, newalt = self.extract_vcf_variant('+', pos, ref, alt)
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111 zyg = self.homo_hetro(sample_data[gt_field_no])
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112 depth, alt_reads, af = self.extract_read_info(sample_data, gt, gts, genotype_fields)
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113
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114 wdict = {'tags':tag,
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115 'chrom':chrom,
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116 'pos':newpos,
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117 'ref_base':newref,
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118 'alt_base':newalt,
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119 'sample_id':sample,
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120 'phred': qual,
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121 'filter': filter,
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122 'zygosity': zyg,
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123 'tot_reads': depth,
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124 'alt_reads': alt_reads,
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125 'af': af,
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126 }
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127 all_wdicts.append(wdict)
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128 return all_wdicts
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129
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130 #The vcf genotype string has a call for each allele separated by '\' or '/'
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131 #If the call is the same for all allels, return 'hom' otherwise 'het'
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132 def homo_hetro(self, gt_str):
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133 if '.' in gt_str:
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134 return '';
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135
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136 gts = gt_str.strip().replace('/', '|').split('|')
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137 for gt in gts:
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138 if gt != gts[0]:
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139 return 'het'
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140 return 'hom'
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141
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142 #Extract read depth, allele count, and allele frequency from optional VCR information
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143 def extract_read_info (self, sample_data, gt, gts, genotype_fields):
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144 depth = ''
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145 alt_reads = ''
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146 ref_reads = ''
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147 af = ''
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148
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149 #AD contains 2 values usually ref count and alt count unless there are
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150 #multiple alts then it will have alt 1 then alt 2.
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151 if 'AD' in genotype_fields and genotype_fields['AD'] <= len(sample_data):
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152 if 0 in gts.keys():
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153 #if part of the genotype is reference, then AD will have #ref reads, #alt reads
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154 ref_reads = sample_data[genotype_fields['AD']].split(',')[0]
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155 alt_reads = sample_data[genotype_fields['AD']].split(',')[1]
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156 elif gt == max(gts.keys()):
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157 #if geontype has multiple alt bases, then AD will have #alt1 reads, #alt2 reads
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158 alt_reads = sample_data[genotype_fields['AD']].split(',')[1]
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159 else:
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160 alt_reads = sample_data[genotype_fields['AD']].split(',')[0]
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161
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162 if 'DP' in genotype_fields and genotype_fields['DP'] <= len(sample_data):
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163 depth = sample_data[genotype_fields['DP']]
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164 elif alt_reads != '' and ref_reads != '':
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165 #if DP is not present but we have alt and ref reads count, dp = ref+alt
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166 depth = int(alt_reads) + int(ref_reads)
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167
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168 if 'AF' in genotype_fields and genotype_fields['AF'] <= len(sample_data):
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169 af = float(sample_data[genotype_fields['AF']] )
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170 elif depth != '' and alt_reads != '':
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171 #if AF not specified, calc it from alt and ref reads
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172 af = float(alt_reads) / float(depth)
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173
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174 return depth, alt_reads, af
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175
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176 def extract_vcf_variant (self, strand, pos, ref, alt):
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177
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178 reflen = len(ref)
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179 altlen = len(alt)
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180
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181 # Returns without change if same single nucleotide for ref and alt.
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182 if reflen == 1 and altlen == 1 and ref == alt:
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183 return pos, ref, alt
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184
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185 # Trimming from the start and then the end of the sequence
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186 # where the sequences overlap with the same nucleotides
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187 new_ref2, new_alt2, new_pos = \
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188 self.trimming_vcf_input(ref, alt, pos, strand)
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189
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190 if new_ref2 == '':
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191 new_ref2 = '-'
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192 if new_alt2 == '':
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193 new_alt2 = '-'
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194
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195 return new_pos, new_ref2, new_alt2
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196
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197 # This function looks at the ref and alt sequences and removes
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198 # where the overlapping sequences contain the same nucleotide.
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199 # This trims from the end first but does not remove the first nucleotide
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200 # because based on the format of VCF input the
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201 # first nucleotide of the ref and alt sequence occur
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202 # at the position specified.
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203 # End removed first, not the first nucleotide
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204 # Front removed and position changed
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205 def trimming_vcf_input(self, ref, alt, pos, strand):
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206 pos = int(pos)
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207 reflen = len(ref)
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208 altlen = len(alt)
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209 minlen = min(reflen, altlen)
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210 new_ref = ref
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211 new_alt = alt
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212 new_pos = pos
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213 # Trims from the end. Except don't remove the first nucleotide.
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214 # 1:6530968 CTCA -> GTCTCA becomes C -> GTC.
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215 for nt_pos in range(0, minlen - 1):
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216 if ref[reflen - nt_pos - 1] == alt[altlen - nt_pos - 1]:
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217 new_ref = ref[:reflen - nt_pos - 1]
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218 new_alt = alt[:altlen - nt_pos - 1]
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219 else:
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220 break
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221 new_ref_len = len(new_ref)
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222 new_alt_len = len(new_alt)
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223 minlen = min(new_ref_len, new_alt_len)
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224 new_ref2 = new_ref
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225 new_alt2 = new_alt
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226 # Trims from the start. 1:6530968 G -> GT becomes 1:6530969 - -> T.
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227 for nt_pos in range(0, minlen):
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228 if new_ref[nt_pos] == new_alt[nt_pos]:
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229 if strand == '+':
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230 new_pos += 1
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231 elif strand == '-':
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232 new_pos -= 1
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233 new_ref2 = new_ref[nt_pos + 1:]
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234 new_alt2 = new_alt[nt_pos + 1:]
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235 else:
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236 new_ref2 = new_ref[nt_pos:]
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237 new_alt2 = new_alt[nt_pos:]
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238 break
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239 return new_ref2, new_alt2, new_pos
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240
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241
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242 if __name__ == "__main__":
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243 c = CravatConverter() |
