govcf 0.10.0

govcf

govcf - Variant Call File "call" generator

This is a proprietary package that is available from GenomOncology and works with our Knowledge Management System.

For more information about licensing please contact us at:

[e-mail]

Additional proprietary projects available for download via pypi include:

• GO SDK - GenomOncology Software Development Kit
• GO CLI - GenomOncology Command Line Interface

Our open source projects include:

• Related - Nested Object Models in Python with dictionary, YAML, and JSON transformation support
• Specd - Swagger v2 Specification Directories
• Rigor - HTTP-based DSL for for validating RESTful APIs

Overview

GenomOncology Variant Call File (VCF) generator built on top of the VCF parser within the pysam project. The generator yields two record types as indicated by the __type__ dictionary attribute:

• Header (1 per VCF file)
• Call (1 per unique sample alt)

The header includes the following information:

• __child__: the type of the records that will follow the header.
• config: any configuration fields provided to the generator.
• file_path: the file location of the VCF.
• formats: the meta data of the FORMAT fields in the header.
• info: the meta data of the INFO fields in the header.
• types: the field type of all of the fields found in the INFO or FORMAT.

A call is the representation of a single ALT allele for a given sample. The calls are generated for each VCF record by iterating each of the samples and yielding a call for each unique ALT index specified by the GT (genotype) field.

A call includes the following fields:

• alt: alternate allele
• chr: chromosome
• filters: filters provided, including None for '.'
• info: info value fields
• is_het: boolean that is true when allele is heterozygous (e.g. 0/1)
• is_phased: boolean that indicates whether phased (|) or unphased (/)
• quality: quality value
• ref: reference allele
• rs_id: ID field
• sample_name: name of the sample column
• start: start position

This package also has a class called BedFilter which can be passed into the iterator functions that filters records by chromosome and start position and only yields calls that fall within the range specified by the BED file.

Quick Example

The following example is what the parsing of the example provided at the top of the VCF Specification document here:

https://samtools.github.io/hts-specs/VCFv4.2.pdf

Here is the VCF:

##fileformat=VCFv4.2
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	NA00001	NA00002	NA00003
20	14370	rs6054257	G	A	29	PASS	NS=3;DP=14;AF=0.5;DB;H2	GT:GQ:DP:HQ	0|0:48:1:51,51	1|0:48:8:51,51	1/1:43:5:.,.
20	17330	.	T	A	3	q10	NS=3;DP=11;AF=0.017	GT:GQ:DP:HQ	0|0:49:3:58,50	0|1:3:5:65,3	0/0:41:3
20	1110696	rs6040355	A	G,T	67	PASS	NS=2;DP=10;AF=0.333,0.667;AA=T;DB	GT:GQ:DP:HQ	1|2:21:6:23,27	2|1:2:0:18,2	2/2:35:4
20	1230237	.	T	.	47	PASS	NS=3;DP=13;AA=T	GT:GQ:DP:HQ	0|0:54:7:56,60	0|0:48:4:51,51	0/0:61:2
20	1234567	microsat1	GTC	G,GTCT	50	PASS	NS=3;DP=9;AA=G;H2	GT:GQ:DP	0/1:35:4	0/2:17:2	1/1:40:3

Here is some example python code:

from govcf import iterate_vcf_calls, BEDFilter
from pprint import pprint

bed_filter = BEDFilter("panel.bed")

for record in iterate_vcf_calls("tests/vcfs/spec.vcf", bed_filter=bed_filter):
    pprint(record)

Yields the following results:

{'__child__': 'CALL',
 '__type__': 'HEADER',
 'config': {'include_vaf': True},
 'file_path': '/Users/ian/code/govcf/tests/vcfs/spec.vcf',
 'formats': {'DP': {'description': 'Read Depth',
                    'id': 2,
                    'name': 'DP',
                    'number': 1,
                    'type': 'Integer'},
             'GQ': {'description': 'Genotype Quality',
                    'id': 10,
                    'name': 'GQ',
                    'number': 1,
                    'type': 'Integer'},
             'GT': {'description': 'Genotype',
                    'id': 9,
                    'name': 'GT',
                    'number': 1,
                    'type': 'String'},
             'HQ': {'description': 'Haplotype Quality',
                    'id': 11,
                    'name': 'HQ',
                    'number': 2,
                    'type': 'Integer'}},
 'info': {'AA': {'description': 'Ancestral Allele',
                 'id': 4,
                 'name': 'AA',
                 'number': 1,
                 'type': 'String'},
          'AF': {'description': 'Allele Frequency',
                 'id': 3,
                 'name': 'AF',
                 'number': 'A',
                 'type': 'Float'},
          'DB': {'description': 'dbSNP membership, build 129',
                 'id': 5,
                 'name': 'DB',
                 'number': 0,
                 'type': 'Flag'},
          'DP': {'description': 'Total Depth',
                 'id': 2,
                 'name': 'DP',
                 'number': 1,
                 'type': 'Integer'},
          'H2': {'description': 'HapMap2 membership',
                 'id': 6,
                 'name': 'H2',
                 'number': 0,
                 'type': 'Flag'},
          'NS': {'description': 'Number of Samples With Data',
                 'id': 1,
                 'name': 'NS',
                 'number': 1,
                 'type': 'Integer'}},
 'types': {'AA': 'string',
           'AF': 'float',
           'DB': 'boolean',
           'DP': 'int',
           'GQ': 'int',
           'H2': 'boolean',
           'HQ': 'mint',
           'NS': 'int'}}
{'__type__': 'CALL',
 'alt': 'A',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AF': 0.5,
          'DB': True,
          'DP': 8,
          'GQ': 48,
          'H2': True,
          'HQ': (51, 51),
          'NS': 3},
 'is_het': True,
 'is_phased': True,
 'quality': 29.0,
 'ref': 'G',
 'rs_id': 'rs6054257',
 'sample_name': 'NA00002',
 'start': 14370}
{'__type__': 'CALL',
 'alt': 'A',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AF': 0.5,
          'DB': True,
          'DP': 5,
          'GQ': 43,
          'H2': True,
          'HQ': (None, None),
          'NS': 3},
 'is_het': False,
 'is_phased': False,
 'quality': 29.0,
 'ref': 'G',
 'rs_id': 'rs6054257',
 'sample_name': 'NA00003',
 'start': 14370}
{'__type__': 'CALL',
 'alt': 'A',
 'chr': '20',
 'filters': ['q10'],
 'info': {'AF': 0.017000000923871994,
          'DP': 5,
          'GQ': 3,
          'HQ': (65, 3),
          'NS': 3},
 'is_het': True,
 'is_phased': True,
 'quality': 3.0,
 'ref': 'T',
 'rs_id': None,
 'sample_name': 'NA00002',
 'start': 17330}
{'__type__': 'CALL',
 'alt': 'G',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'T',
          'AF': 0.3330000042915344,
          'DB': True,
          'DP': 6,
          'GQ': 21,
          'HQ': (23, 27),
          'NS': 2},
 'is_het': True,
 'is_phased': True,
 'quality': 67.0,
 'ref': 'A',
 'rs_id': 'rs6040355',
 'sample_name': 'NA00001',
 'start': 1110696}
{'__type__': 'CALL',
 'alt': 'T',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'T',
          'AF': 0.6669999957084656,
          'DB': True,
          'DP': 6,
          'GQ': 21,
          'HQ': (23, 27),
          'NS': 2},
 'is_het': True,
 'is_phased': True,
 'quality': 67.0,
 'ref': 'A',
 'rs_id': 'rs6040355',
 'sample_name': 'NA00001',
 'start': 1110696}
{'__type__': 'CALL',
 'alt': 'G',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'T',
          'AF': 0.3330000042915344,
          'DB': True,
          'DP': 0,
          'GQ': 2,
          'HQ': (18, 2),
          'NS': 2},
 'is_het': True,
 'is_phased': True,
 'quality': 67.0,
 'ref': 'A',
 'rs_id': 'rs6040355',
 'sample_name': 'NA00002',
 'start': 1110696}
{'__type__': 'CALL',
 'alt': 'T',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'T',
          'AF': 0.6669999957084656,
          'DB': True,
          'DP': 0,
          'GQ': 2,
          'HQ': (18, 2),
          'NS': 2},
 'is_het': True,
 'is_phased': True,
 'quality': 67.0,
 'ref': 'A',
 'rs_id': 'rs6040355',
 'sample_name': 'NA00002',
 'start': 1110696}
{'__type__': 'CALL',
 'alt': 'T',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'T',
          'AF': 0.6669999957084656,
          'DB': True,
          'DP': 4,
          'GQ': 35,
          'HQ': (None,),
          'NS': 2},
 'is_het': False,
 'is_phased': False,
 'quality': 67.0,
 'ref': 'A',
 'rs_id': 'rs6040355',
 'sample_name': 'NA00003',
 'start': 1110696}
{'__type__': 'CALL',
 'alt': 'G',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'G', 'DP': 4, 'GQ': 35, 'H2': True, 'NS': 3},
 'is_het': True,
 'is_phased': False,
 'quality': 50.0,
 'ref': 'GTC',
 'rs_id': 'microsat1',
 'sample_name': 'NA00001',
 'start': 1234567}
{'__type__': 'CALL',
 'alt': 'GTCT',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'G', 'DP': 2, 'GQ': 17, 'H2': True, 'NS': 3},
 'is_het': True,
 'is_phased': False,
 'quality': 50.0,
 'ref': 'GTC',
 'rs_id': 'microsat1',
 'sample_name': 'NA00002',
 'start': 1234567}
{'__type__': 'CALL',
 'alt': 'G',
 'chr': '20',
 'filters': ['PASS'],
 'info': {'AA': 'G', 'DP': 3, 'GQ': 40, 'H2': True, 'NS': 3},
 'is_het': False,
 'is_phased': False,
 'quality': 50.0,
 'ref': 'GTC',
 'rs_id': 'microsat1',
 'sample_name': 'NA00003',
 'start': 1234567}