VCF Parser

Small library for parsing vcf files. Based on PyVCF

usage examples:

- Split variants lines with multiple alleles
- Create vcf files from a python environment and print them
- Parse through variants and retrieve relevant information

Installation

pip install vcf_parser

or

>git clone https://github.com/moonso/vcf_parser.git
>cd vcf_parser
>python setup.py install

Usage

If used within a python environment:

>from vcf_parser import VCFParser
>my_parser = VCFParser(infile='infile.vcf', split_variants=True, check_info=True)
>for variant in my_parser:
    print(variant)

or used as a command line tool

vcf_parser examples/test_vcf.vcf --split

Prints a new vcf with splitted variants to screen.

Vcf parser is really a lightweight version of PyVCF with most of it's code borrowed and modified from there.

The idea was to make a faster and more flexible tool that mostly work with python dictionaries.

It is easy to access information for each variant, edit the information and edit the headers.

Basic function

Returns dictionary with the vcf info for each variant. To split the multiallelic calls(and accurate splitting of INFO field including the VEP CSQ fiels) use:

my_parser = VCFParser(infile='infile.vcf', split_variants=True)

The ordinary vcf entrys is stored by there header names, like

variant['CHROM']
variant['ALT']

etc.

Genotypes

The genotype information is converted to a genotype object and stored in a dictionary

variant['genotypes']

and looks like:

'genotypes': {'father': <genotype_object>,
              'mother': <genotype_object>,
              'proband': <genotype_object>}

The genotype class have the following attributes for phrasing common questions:

- genotype STRING (Same as in VCF-standard)
- allele_1 STRING (Base on allele 1)
- allele_2 STRING (Base on allele 2)
- nocall BOOL
- heterozygote BOOL 
- homo_alt BOOL (If individual is homozygote alternative)
- homo_ref BOOL (If individual is homozygote reference)
- has_variant BOOL (If individual is called and not homozygote reference)
- ref_depth INT
- alt_depth INT
- phred_likelihoods LIST with FLOAT
- depth_of_coverage INT
- genotype_quality FLOAT
- phased BOOL

Vep info

Vep information, if present, is parsed into

variant['vep_dict']

and looks like (depending on how vep was run):

'vep_info': {<alternative_allele>: {
                        'Allele': 'G',
                        'Amino_acids': '',
                        'CDS_position': '',
                        'Codons': '',
                        'Consequence': 'downstream_gene_variant',
                        'DISTANCE': '3084',
                        'EXON': '',
                        'Existing_variation': '',
                        'Feature': 'NM_015658.3',
                        'Feature_type': 'Transcript',
                        'Gene': '26155',
                        'HGVSc': '',
                        'HGVSp': '',
                        'INTRON': '',
                        'PolyPhen': '',
                        'Protein_position': '',
                        'SIFT': '',
                        'STRAND': '-1',
                        'SYMBOL': 'NOC2L',
                        'SYMBOL_SOURCE': '',
                        'cDNA_position': ''},
              <alternative_allele>: {
                          'Allele': 'G',
                         'Amino_acids': '',
                         'CDS_position': '',
                         'Codons': '',
                         'Consequence': 'intron_variant',
                         'DISTANCE': '',
                         'EXON': '',
                         'Existing_variation': '',
                         'Feature': 'NM_152486.2',
                         'Feature_type': 'Transcript',
                         'Gene': '148398',
                         'HGVSc': 'NM_152486.2:c.707-25A>G',
                         'HGVSp': '',
                         'INTRON': '7/13',
                         'PolyPhen': '',
                         'Protein_position': '',
                         'SIFT': '',
                         'STRAND': '1',
                         'SYMBOL': 'SAMD11',
                         'SYMBOL_SOURCE': '',
                         'cDNA_position': ''
                     }
                 }

Info field

INFO field is parsed into a dictionary The keys are the names of the info field and values are lists separated on ','.

variant['info_dict]

and looks like

'info_dict': {'AC': ['1'],
               'AF': ['0.167'],
               'AN': ['6'],
               'BaseQRankSum': ['2.286'],
               'DB': [],
               'DP': ['1306'],
               'FS': ['1.539'],
               'InbreedingCoeff': ['0.1379'],
               'MQ': ['39.83'],
               'MQ0': ['0'],
               'MQRankSum': ['-2.146'],
               'POSITIVE_TRAIN_SITE': [],
               'QD': ['29.57'],
               'ReadPosRankSum': ['0.897'],
               'VQSLOD': ['4.52'],
               'culprit': ['FS'],
               'set': ['variant']}

Print a vcf in it´s original format:

my_parser = parser.VCFParser(infile='infile.vcf')
for line in my_parser.metadata.print_header():
    print(line)
for variant in my_parser:
    print('\t'.join([[variant[head] for head in my_parser.header]))

Build a vcf file from scratch

One can use vcf_parser to build vcf files from scratch. A vcf file must allways have the "fileformat" header, so start by initializing a vcf parser with the name of the fileformat like

from vcf_parser import VCFParser

> my_vcf = VCFParser(fileformat='VCFv4.2')

Add metadata information:

Adding INFO field:

    my_parser.add_info('my_new_id', <number>, <type>, <description>)

Where 'number', 'type' and 'description' follows the VCF specification.

Add a filter:

    my_parser.add_filter('my_filter', <description>)

Add a arbitrary metadata line:

    my_parser.add_filter(key='my_data_line', value="The description")

example:

from vcf_parser import VCFParser

> my_vcf = VCFParser(fileformat='VCFv4.2')
> my_vcf.metadata.add_filedate(filedate='20150607')
> my_vcf.metadata.add_info(info_id='MQ', number='1', entry_type='Float', description="RMS Mapping Quality")
> my_vcf.metadata.add_filter(filter_id="MY_FILTER", description="The filter description")
> my_vcf.metadata.add_format(format_id="DP", number='1', entry_type='Integer', description="The read depth")
> my_vcf.metadata.add_alt(alt_id="MY_ALTERNATIVE", description="The alternative description")
> my_vcf.metadata.add_meta_line_(key="filedate", value="20150607")