def __init__(self, *args, **kwargs):
self.sample_id = kwargs.pop('sample_id')
self.vcf_sample = kwargs.pop('vcf_sample')
self.now = datetime.now()
super(ResultStream, self).__init__(*args, **kwargs)
self.genotypes = dict(Genotype.objects.values_list('value', 'pk'))
self.variants = VariantCache()
def __init__(self, *args, **kwargs):
self.sample_id = kwargs.pop('sample_id')
self.vcf_sample = kwargs.pop('vcf_sample')
self.now = datetime.now()
super(ResultStream, self).__init__(*args, **kwargs)
self.genotypes = dict(Genotype.objects.values_list('value', 'pk'))
self.variants = VariantCache()
class ResultStream(VCFPGCopyEditor):
vcf_fields = ('CHROM', 'POS', 'REF', 'ALT')
info_fields = ('DB', 'DS', 'DP', 'Dels', 'MQ', 'MQ0', 'BaseQRankSum',
'MQRankSum', 'ReadPosRankSum', 'SB', 'Hrun',
'HaplotypeScore', 'QD', 'FS', 'BaseCounts')
output_columns = ('in_dbsnp', 'downsampling', 'raw_read_depth',
'spanning_deletions', 'mq', 'mq0', 'baseq_rank_sum',
'mq_rank_sum', 'read_pos_rank_sum', 'strand_bias',
'homopolymer_run', 'haplotype_score', 'quality_by_depth',
'fisher_strand', 'base_counts', 'variant_id',
'sample_id', 'read_depth', 'quality', 'genotype_id',
'genotype_quality', 'coverage_ref', 'coverage_alt',
'phred_scaled_likelihood', 'created', 'modified')
def __init__(self, *args, **kwargs):
self.sample_id = kwargs.pop('sample_id')
self.vcf_sample = kwargs.pop('vcf_sample')
self.now = datetime.now()
super(ResultStream, self).__init__(*args, **kwargs)
self.genotypes = dict(Genotype.objects.values_list('value', 'pk'))
self.variants = VariantCache()
def process_line(self, record):
# we are revisiting the same line once for each sample
# until I figure out how the cleaning and loading will
# work otherwise
# Ensures the cache is updated and available
self.variants.ensure_cache(record)
# Calculate the MD5 of the variant itself (not the record)
md5 = calculate_md5(record)
# Ensure the variant exists
variant_id = self.variants.get(md5)
assert variant_id is not None
cleaned = super(ResultStream, self).process_line(record)
# Remove variant specific parts
cleaned = cleaned[4:]
# can these be indexed?
call = record.genotype(self.vcf_sample)
# Already seen this variant for this sample, otherwise we would get a
# duplicate key value violation in sample_result.
if Result.objects.filter(
variant=variant_id, sample=self.sample_id).exists():
return None
# The possibility for multiple alleles in these wide vcfs is almost
# infinite so we need to triage the really weird ones into having a
# reference allele "0/#" or being off the map entirely "#/#"".
gt = getattr(call, 'GT', None)
if gt:
try:
keyed_geno = self.genotypes[gt]
except KeyError:
if gt.startswith('0'):
keyed_geno = self.genotypes['0/#']
else:
keyed_geno = self.genotypes['#/#']
else:
keyed_geno = None
dp = getattr(call, 'DP', None)
gq = getattr(call, 'GQ', None)
ad = getattr(call, 'AD', None)
if ad and len(ad) > 1:
ad0 = ad[0]
ad1 = ad[1]
else:
ad0 = None
ad1 = None
pl = getattr(call, 'PL', None)
if pl:
pl = ','.join([str(x) for x in pl])
# Append remaining columns
other = [variant_id, self.sample_id, dp, record.QUAL, keyed_geno, gq,
ad0, ad1, pl, self.now, self.now]
cleaned.extend([self.process_column('', x) for x in other])
return cleaned
def readline(self, size=-1):
"Ignore the `size` since a complete line must be processed."
while True:
try:
record = next(self.reader)
except StopIteration:
break
# Ensure this is a valid record
if checks.record_is_valid(record):
# Process the line
cleaned = self.process_line(record)
if cleaned:
return self.outdel.join([str(x) for x in cleaned]) + '\n'
return ''
class ResultStream(VCFPGCopyEditor):
vcf_fields = ('CHROM', 'POS', 'REF', 'ALT')
info_fields = ('DB', 'DS', 'DP', 'Dels', 'MQ', 'MQ0', 'BaseQRankSum',
'MQRankSum', 'ReadPosRankSum', 'SB', 'Hrun', 'HaplotypeScore',
'QD', 'FS', 'BaseCounts')
output_columns = ('in_dbsnp', 'downsampling', 'raw_read_depth',
'spanning_deletions', 'mq', 'mq0', 'baseq_rank_sum', 'mq_rank_sum',
'read_pos_rank_sum', 'strand_bias', 'homopolymer_run', 'haplotype_score',
'quality_by_depth', 'fisher_strand', 'base_counts', 'variant_id',
'sample_id', 'read_depth', 'quality', 'genotype_id', 'genotype_quality',
'coverage_ref', 'coverage_alt', 'phred_scaled_likelihood',
'created', 'modified')
def __init__(self, *args, **kwargs):
self.sample_id = kwargs.pop('sample_id')
self.vcf_sample = kwargs.pop('vcf_sample')
self.now = datetime.now()
super(ResultStream, self).__init__(*args, **kwargs)
self.genotypes = dict(Genotype.objects.values_list('value', 'pk'))
self.variants = VariantCache()
def process_line(self, record):
# we are revisiting the same line once for each sample
# until I figure out how the cleaning and loading will
# work otherwise
# Ensures the cache is updated and available
self.variants.ensure_cache(record)
# Calculate the MD5 of the variant itself (not the record)
md5 = calculate_md5(record)
# Ensure the variant exists
variant_id = self.variants.get(md5)
assert variant_id is not None
cleaned = super(ResultStream, self).process_line(record)
# Remove variant specific parts
cleaned = cleaned[4:]
# can these be indexed?
call = record.genotype(self.vcf_sample)
#for sample in record.samples:
# if str(sample.sample) == str(self.vcf_sample):
# call = sample
# break
#log.debug('record {0} annotating sample {1} with variant {2} details {3}'.format(record,self.vcf_sample, variant_id,call))
# empty values cause KeyErrors#
if None in (call['AD'],call['DP'],call['GQ'],call['GT'],call['PL']):
return None
# already seen this variant for this sample
# otherwise we would get a duplicate key value violation in sample_result
if Result.objects.filter(variant=variant_id,sample=self.sample_id).exists():
return None
# the possibility for multiple alleles in these wide vcfs is almost infinite
# so we need to triage the really weird ones into having a reference allele "0/#"
# or being off the map entirely "#/#""
try:
keyed_geno = self.genotypes[call['GT']]
except KeyError, e:
if call['GT'].startswith('0'):
keyed_geno = self.genotypes['0/#']
else:
keyed_geno = self.genotypes['#/#']
# Append remaining columns
other = [
variant_id,
self.sample_id,
call['DP'],
record.QUAL,
keyed_geno,
call['GQ'],
call['AD'][0],
call['AD'][1],
','.join([str(x) for x in call['PL']]),
self.now,
self.now,
]
cleaned.extend([self.process_column('', x) for x in other])
return cleaned
def setUp(self):
self.vcache = VariantCache()
self.vcache._cache.clear()
class ResultStream(VCFPGCopyEditor):
vcf_fields = ('CHROM', 'POS', 'REF', 'ALT')
info_fields = ('DB', 'DS', 'DP', 'Dels', 'MQ', 'MQ0', 'BaseQRankSum',
'MQRankSum', 'ReadPosRankSum', 'SB', 'Hrun',
'HaplotypeScore', 'QD', 'FS', 'BaseCounts')
output_columns = ('in_dbsnp', 'downsampling', 'raw_read_depth',
'spanning_deletions', 'mq', 'mq0', 'baseq_rank_sum',
'mq_rank_sum', 'read_pos_rank_sum', 'strand_bias',
'homopolymer_run', 'haplotype_score', 'quality_by_depth',
'fisher_strand', 'base_counts', 'variant_id',
'sample_id', 'read_depth', 'quality', 'genotype_id',
'genotype_quality', 'coverage_ref', 'coverage_alt',
'phred_scaled_likelihood', 'created', 'modified')
def __init__(self, *args, **kwargs):
self.sample_id = kwargs.pop('sample_id')
self.vcf_sample = kwargs.pop('vcf_sample')
self.now = datetime.now()
super(ResultStream, self).__init__(*args, **kwargs)
self.genotypes = dict(Genotype.objects.values_list('value', 'pk'))
self.variants = VariantCache()
def process_line(self, record):
# we are revisiting the same line once for each sample
# until I figure out how the cleaning and loading will
# work otherwise
# Ensures the cache is updated and available
self.variants.ensure_cache(record)
# Calculate the MD5 of the variant itself (not the record)
md5 = calculate_md5(record)
# Ensure the variant exists
variant_id = self.variants.get(md5)
assert variant_id is not None
cleaned = super(ResultStream, self).process_line(record)
# Remove variant specific parts
cleaned = cleaned[4:]
# can these be indexed?
call = record.genotype(self.vcf_sample)
#for sample in record.samples:
# if str(sample.sample) == str(self.vcf_sample):
# call = sample
# break
#log.debug('record {0} annotating sample {1} with variant {2} details {3}'.format(record,self.vcf_sample, variant_id,call))
# empty values cause KeyErrors#
if None in (call['AD'], call['DP'], call['GQ'], call['GT'],
call['PL']):
return None
# already seen this variant for this sample
# otherwise we would get a duplicate key value violation in sample_result
if Result.objects.filter(variant=variant_id,
sample=self.sample_id).exists():
return None
# the possibility for multiple alleles in these wide vcfs is almost infinite
# so we need to triage the really weird ones into having a reference allele "0/#"
# or being off the map entirely "#/#""
try:
keyed_geno = self.genotypes[call['GT']]
except KeyError, e:
if call['GT'].startswith('0'):
keyed_geno = self.genotypes['0/#']
else:
keyed_geno = self.genotypes['#/#']
# Append remaining columns
other = [
variant_id,
self.sample_id,
call['DP'],
record.QUAL,
keyed_geno,
call['GQ'],
call['AD'][0],
call['AD'][1],
','.join([str(x) for x in call['PL']]),
self.now,
self.now,
]
cleaned.extend([self.process_column('', x) for x in other])
return cleaned
