# HG changeset patch # User iuc # Date 1548090347 18000 # Node ID 7c5e867820cf959cd76004f8ce98071761e5a87b # Parent ab2f908f0b083bb5391bf2539ce61aa6d2e48497 planemo upload for repository https://github.com/galaxyproject/iuc/tree/master/tools/varscan commit f5e4d8903b6d69b0507f6a8fc4c2533fc7a15dfa diff -r ab2f908f0b08 -r 7c5e867820cf varscan.py --- a/varscan.py Fri Jan 18 19:41:30 2019 -0500 +++ b/varscan.py Mon Jan 21 12:05:47 2019 -0500 @@ -443,36 +443,60 @@ # VarScan with pysam.VariantFile(varcall_template, 'r') as original_data: varscan_header = original_data.header + # don't propagate non-standard and redundant FORMAT keys written + # by VarScan + varscan_header.formats.remove_header('AD') + varscan_header.formats.remove_header('FREQ') + varscan_header.formats.remove_header('RD') + varscan_header.formats.remove_header('DP4') for sample in varscan_header.samples: common_header.samples.add(sample) common_header.merge(varscan_header) - # don't propagate non-standard and redundant FORMAT keys written - # by VarScan - common_header.formats.remove_header('FREQ') - common_header.formats.remove_header('RD') - common_header.formats.remove_header('DP4') return common_header - def _fix_read_gt_fields(self, read): + def _fix_record_gt_fields(self, record): """Migrate non-standard genotype fields to standard ones.""" - for gt_field in read.samples.values(): + # The key issue to consider here is that we need to modify + # genotype field values on a per-sample basis, but htslib + # reserves memory for the values of all samples upon the first + # modification of the field in the variant record. + # => We need to calculate all values first, then fill each + # genotype field starting with the sample with the largest value. + new_gt_fields = {'AD': [], 'ADF': [], 'ADR': []} + # store the current genotype field contents for each sample + per_sample_gts = record.samples.values() + # calculate and store the new genotype field values + for gt_field in per_sample_gts: # generate a standard AD field by combining VarScan's # RD and non-standard AD fields - gt_field['AD'] = (gt_field['RD'], gt_field['AD'][0]) + new_gt_fields['AD'].append((gt_field['RD'], gt_field['AD'][0])) # split VarScan's DP4 field into the standard fields # ADF and ADR - gt_field['ADF'] = ( - int(gt_field['DP4'][0]), int(gt_field['DP4'][2]) + new_gt_fields['ADF'].append( + (int(gt_field['DP4'][0]), int(gt_field['DP4'][2])) + ) + new_gt_fields['ADR'].append( + (int(gt_field['DP4'][1]), int(gt_field['DP4'][3])) ) - gt_field['ADR'] = ( - int(gt_field['DP4'][1]), int(gt_field['DP4'][3]) - ) + # Modify the record's genotype fields. + # For each field, modify the sample containing the largest + # value for the field first. + # Without this precaution we could trigger: + # "bcf_update_format: Assertion `!fmt->p_free' failed." + # in vcf.c of htslib resulting in a core dump. + for field in sorted(new_gt_fields): + for new_field, sample_fields in sorted( + zip(new_gt_fields[field], per_sample_gts), + key=lambda x: max(x[0]), + reverse=True + ): + sample_fields[field] = new_field # remove redundant fields # FREQ is easy to calculate from AD - del read.format['FREQ'] - del read.format['RD'] - del read.format['DP4'] + del record.format['FREQ'] + del record.format['RD'] + del record.format['DP4'] def pileup_masker(self, mask): def apply_mask_on_pileup(piled_items): @@ -845,7 +869,7 @@ ), **filter_args ): - self._fix_read_gt_fields(record) + self._fix_record_gt_fields(record) o.write(str(record)) try: os.remove(snp_f) @@ -871,7 +895,7 @@ for record in apply_filters( invcf, **filter_args ): - self._fix_read_gt_fields(record) + self._fix_record_gt_fields(record) o.write(str(record)) try: os.remove(f) @@ -892,7 +916,7 @@ for record in apply_filters( self._indel_flagged_records(invcf), **filter_args ): - self._fix_read_gt_fields(record) + self._fix_record_gt_fields(record) o.write(str(record)) try: os.remove(f)