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A VCFv4.0 parser for Python.

The intent of this module is to mimic the csv module in the Python stdlib, as opposed to more flexible serialization formats like JSON or YAML. vcf will attempt to parse the content of each record based on the data types specified in the meta-information lines -- specifically the ##INFO and ##FORMAT lines. If these lines are missing or incomplete, it will check against the reserved types mentioned in the spec. Failing that, it will just return strings.

There is currently one piece of interface: Reader. It takes a file-like object and acts as a reader:

>>> import vcf
>>> vcf_reader = vcf.Reader(open('test/example.vcf', 'rb'))
>>> for record in vcf_reader:
...     print record
Record(CHROM=20, POS=14370, REF=G, ALT=['A'])
Record(CHROM=20, POS=17330, REF=T, ALT=['A'])
Record(CHROM=20, POS=1110696, REF=A, ALT=['G', 'T'])
Record(CHROM=20, POS=1230237, REF=T, ALT=['.'])
Record(CHROM=20, POS=1234567, REF=GTCT, ALT=['G', 'GTACT'])

This produces a great deal of information, but it is conveniently accessed. The attributes of a Record are the 8 fixed fields from the VCF spec plus two more. That is:

  • Record.CHROM
  • Record.POS
  • Record.ID
  • Record.REF
  • Record.ALT
  • Record.QUAL
  • Record.FILTER
  • Record.INFO

plus three more attributes to handle genotype information:

  • Record.FORMAT
  • Record.samples
  • Record.genotype

samples and genotypes, not being the title of any column, is left lowercase. The format of the fixed fields is from the spec. Comma-separated lists in the VCF are converted to lists. In particular, one-entry VCF lists are converted to one-entry Python lists (see, e.g., Record.ALT). Semicolon-delimited lists of key=value pairs are converted to Python dictionaries, with flags being given a True value. Integers and floats are handled exactly as you'd expect:

>>> vcf_reader = vcf.Reader(open('test/example.vcf', 'rb'))
>>> record = vcf_reader.next()
>>> print record.POS
14370
>>> print record.ALT
['A']
>>> print record.INFO['AF']
[0.5]

record.FORMAT will be a string specifying the format of the genotype fields. In case the FORMAT column does not exist, record.FORMAT is None. Finally, record.samples is a list of dictionaries containing the parsed sample column and record.genotype is a way of looking up genotypes by sample name:

>>> record = vcf_reader.next()
>>> for sample in record.samples:
...     print sample['GT']
0|0
0|1
0/0
>>> print record.genotype('NA00001')['GT']
0|0

Metadata regarding the VCF file itself can be investigated through the following attributes:

  • Reader.metadata
  • Reader.infos
  • Reader.filters
  • Reader.formats
  • Reader.samples

For example:

>>> vcf_reader.metadata['fileDate']
'20090805'
>>> vcf_reader.samples
['NA00001', 'NA00002', 'NA00003']
>>> vcf_reader.filters
{'q10': Filter(id='q10', desc='Quality below 10'), 's50': Filter(id='s50', desc='Less than 50% of samples have data')}
>>> vcf_reader.infos['AA'].desc
'Ancestral Allele'

Random access is supported for files with tabix indexes. Simply call fetch for the region you are interested in:

>>> vcf_reader = vcf.Reader(filename='test/tb.vcf.gz')
>>> for record in vcf_reader.fetch('20', 1110696-1, 1230237):
...     print record
Record(CHROM=20, POS=1110696, REF=A, ALT=['G', 'T'])
Record(CHROM=20, POS=1230237, REF=T, ALT=['.'])

An extensible script is available to filter vcf files in vcf_filter.py. VCF filters declared by other packages will be available for use in this script. Please see FILTERS.md for full description.

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