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vcf.py
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#!/usr/bin/env python
'''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]
There are a number of convienience functions for each ``Record`` allowing you to
examine properties of interest::
>>> print record.num_called, record.call_rate, record.num_unknown
3 1.0 0
>>> print record.num_hom_ref, record.num_het, record.num_hom_alt
1 1 1
>>> print record.nucl_diversity, record.aaf
0.6 0.5
>>> print record.get_hets()
[Call(sample=NA00002, GT=1|0)]
``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
The genotypes are represented by ``Call`` objects, which have three attributes: the
corresponding Record ``site``, the sample name in ``sample`` and a dictionary of
call data in ``data``::
>>> call = record.genotype('NA00001')
>>> print call.site
Record(CHROM=20, POS=17330, REF=T, ALT=['A'])
>>> print call.sample
NA00001
>>> print call.data
{'GT': '0|0', 'HQ': [58, 50], 'DP': [3], 'GQ': [49]}
There are also a number of methods::
>>> print call.called, call.gt_type, call.gt_bases, call.phased
True 0 T|T True
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.
'''
import collections
import re
import csv
import gzip
import sys
import itertools
try:
import pysam
except ImportError:
pysam = None
# Metadata parsers/constants
RESERVED_INFO = {
'AA': 'String', 'AC': 'Integer', 'AF': 'Float', 'AN': 'Integer',
'BQ': 'Float', 'CIGAR': 'String', 'DB': 'Flag', 'DP': 'Integer',
'END': 'Integer', 'H2': 'Flag', 'MQ': 'Float', 'MQ0': 'Integer',
'NS': 'Integer', 'SB': 'String', 'SOMATIC': 'Flag', 'VALIDATED': 'Flag'
}
RESERVED_FORMAT = {
'GT': 'String', 'DP': 'Integer', 'FT': 'String', 'GL': 'Float',
'GQ': 'Float', 'HQ': 'Float'
}
_Info = collections.namedtuple('Info', ['id', 'num', 'type', 'desc'])
_Filter = collections.namedtuple('Filter', ['id', 'desc'])
_Format = collections.namedtuple('Format', ['id', 'num', 'type', 'desc'])
class _vcf_metadata_parser(object):
'''Parse the metadat in the header of a VCF file.'''
def __init__(self, aggressive=False):
super(_vcf_metadata_parser, self).__init__()
self.aggro = aggressive
self.info_pattern = re.compile(r'''\#\#INFO=<
ID=(?P<id>[^,]+),
Number=(?P<number>-?\d+|\.|[AG]),
Type=(?P<type>Integer|Float|Flag|Character|String),
Description="(?P<desc>[^"]*)"
>''', re.VERBOSE)
self.filter_pattern = re.compile(r'''\#\#FILTER=<
ID=(?P<id>[^,]+),
Description="(?P<desc>[^"]*)"
>''', re.VERBOSE)
self.format_pattern = re.compile(r'''\#\#FORMAT=<
ID=(?P<id>.+),
Number=(?P<number>-?\d+|\.|[AG]),
Type=(?P<type>.+),
Description="(?P<desc>.*)"
>''', re.VERBOSE)
self.meta_pattern = re.compile(r'''##(?P<key>.+)=(?P<val>.+)''')
def read_info(self, info_string):
'''Read a meta-information INFO line.'''
match = self.info_pattern.match(info_string)
if not match:
raise SyntaxError(
"One of the INFO lines is malformed: {}".format(info_string))
try:
num = int(match.group('number'))
if num < 0:
num = None if self.aggro else '.'
except ValueError:
num = None if self.aggro else '.'
info = _Info(match.group('id'), num,
match.group('type'), match.group('desc'))
return (match.group('id'), info)
def read_filter(self, filter_string):
'''Read a meta-information FILTER line.'''
match = self.filter_pattern.match(filter_string)
if not match:
raise SyntaxError(
"One of the FILTER lines is malformed: {}".format(
filter_string))
filt = _Filter(match.group('id'), match.group('desc'))
return (match.group('id'), filt)
def read_format(self, format_string):
'''Read a meta-information FORMAT line.'''
match = self.format_pattern.match(format_string)
if not match:
raise SyntaxError(
"One of the FORMAT lines is malformed: {}".format(
format_string))
try:
num = int(match.group('number'))
if num < 0:
num = None if self.aggro else '.'
except ValueError:
num = None if self.aggro else '.'
form = _Format(match.group('id'), num,
match.group('type'), match.group('desc'))
return (match.group('id'), form)
def read_meta(self, meta_string):
match = self.meta_pattern.match(meta_string)
return match.group('key'), match.group('val')
class _Call(object):
""" A called genotype, an entry in a VCF file"""
def __init__(self, site, sample, data):
self.site = site
self.sample = sample
self.data = data
self.gt_nums = self.data['GT']
self.called = self.gt_nums is not None and self.gt_nums != "./."
def __repr__(self):
return "Call(sample=%s, GT=%s)" % (self.sample, self.gt_nums)
def __eq__(self, other):
return (self.sample == other.sample and self.data == other.data)
@property
def gt_bases(self):
'''Return the actual genotype alleles.
E.g. if VCF genotype is 0/1, return A/G
'''
# nothing to do if no genotype call
if self.called:
# grab the numeric alleles of the gt string; tokenize by phasing
phase_char = "/" if not self.phased else "|"
(a1, a2) = self.gt_nums.split(phase_char)
# lookup and return the actual DNA alleles
try:
return self.site.alleles[int(a1)] + \
phase_char + \
self.site.alleles[int(a2)]
except:
sys.stderr.write("Allele number not found in list of alleles\n")
else:
return None
@property
def gt_type(self):
'''Return the type of genotype.
hom_ref = 0
het = 1
hom_alt = 2 (we don;t track _which+ ALT)
uncalled = None
'''
# extract the numeric alleles of the gt string
if self.called:
# grab the numeric alleles of the gt string; tokenize by phasing
(a1, a2) = self.gt_nums.split("/") \
if not self.phased else self.gt_nums.split("|")
# infer genotype type from allele numbers
if (int(a1) == 0) and (int(a2) == 0): return 0
elif (int(a1) == 0) and (int(a2) >= 1): return 1
elif (int(a2) == 0) and (int(a1) >= 1): return 1
elif (int(a1) >= 1) and (int(a2) >= 1):
# same alt, so hom_alt
if a1 == a2: return 2
# diff alts, so het
else: return 1
else: return -1
else:
return None
@property
def phased(self):
'''Return a boolean indicating whether or not
the genotype is phased for this sample
'''
return self.data['GT'].find("|") >= 0
def __getitem__(self, key):
""" Lookup value, backwards compatibility """
return self.data[key]
class _Record(object):
""" A set of calls at a site. A row in a VCF file. """
def __init__(self, CHROM, POS, ID, REF, ALT, QUAL, FILTER, INFO, FORMAT, sample_indexes, samples=None):
self.CHROM = CHROM
self.POS = POS
self.ID = ID
self.REF = REF
self.ALT = ALT
self.QUAL = QUAL
self.FILTER = FILTER
self.INFO = INFO
self.FORMAT = FORMAT
# create a list of alleles. [0] = REF, [1:] = ALTS
self.alleles = [self.REF]
self.alleles.extend(self.ALT)
self.samples = samples
self._sample_indexes = sample_indexes
def __str__(self):
return "Record(CHROM=%(CHROM)s, POS=%(POS)s, REF=%(REF)s, ALT=%(ALT)s)" % self.__dict__
def add_format(self, fmt):
self.FORMAT = self.FORMAT + ':' + fmt
def add_filter(self, flt):
if self.FILTER == '.' or self.FILTER == 'PASS':
self.FILTER = ''
else:
self.FILTER = self.FILTER + ';'
self.FILTER = self.FILTER + flt
def add_info(self, info, value=True):
self.INFO[info] = value
def genotype(self, name):
return self.samples[self._sample_indexes[name]]
@property
def num_called(self):
"""Return the number of called samples"""
return sum(s.called for s in self.samples)
@property
def call_rate(self):
""" return the fraction of genotypes that were actually called. """
return float(self.num_called) / float(len(self.samples))
@property
def num_hom_ref(self):
""" return the number of homozygous for ref allele genotypes"""
return len([s for s in self.samples if s.gt_type == 0])
@property
def num_hom_alt(self):
""" return the number of homozygous for alt allele genotypes"""
return len([s for s in self.samples if s.gt_type == 2])
@property
def num_het(self):
""" return the number of heterozygous genotypes"""
return len([s for s in self.samples if s.gt_type == 1])
@property
def num_unknown(self):
""" return the number of unknown genotypes"""
return len([s for s in self.samples if s.gt_type is None])
@property
def aaf(self):
"""Calculate the allele frequency of the alternate allele.
NOTE 1: Punt if more than one alternate allele.
NOTE 2: Denominator calc'ed from _called_ genotypes.
"""
# skip if more than one alternate allele. assumes bi-allelic
if len(self.ALT) > 1:
return None
hom_ref = self.num_hom_ref
het = self.num_het
hom_alt = self.num_hom_alt
num_chroms = float(2.0*self.num_called)
return float(het + 2*hom_alt)/float(num_chroms)
@property
def nucl_diversity(self):
"""
Calculate pi_hat (estimation of nucleotide diversity) for the site.
This metric can be summed across multiple sites to compute regional
nucleotide diversity estimates. For example, pi_hat for all variants
in a given gene.
Derived from:
\"Population Genetics: A Concise Guide, 2nd ed., p.45\"
John Gillespie.
"""
# skip if more than one alternate allele. assumes bi-allelic
if len(self.ALT) > 1:
return None
p = self.aaf
q = 1.0-p
num_chroms = float(2.0*self.num_called)
return float(num_chroms/(num_chroms-1.0)) * (2.0 * p * q)
def get_hom_refs(self):
""" return the list of hom ref genotypes"""
return [s for s in self.samples if s.gt_type == 0]
def get_hom_alts(self):
""" return the list of hom alt genotypes"""
return [s for s in self.samples if s.gt_type == 2]
def get_hets(self):
""" return the list of het genotypes"""
return [s for s in self.samples if s.gt_type == 1]
def get_unknowns(self):
""" return the list of unknown genotypes"""
return [s for s in self.samples if s.gt_type is None]
class Reader(object):
'''Read and parse a VCF v 4.0 file'''
def __init__(self, fsock=None, filename=None, aggressive=False, compressed=False):
super(VCFReader, self).__init__()
if not (fsock or filename):
raise Exception('You must provide at least fsock or filename')
if filename:
self.filename = filename
if fsock is None:
self.reader = file(filename)
if fsock:
self.reader = fsock
if filename is None:
if hasattr(fsock, 'name'):
filename = fsock.name
self.filename = filename
if compressed or (filename and filename.endswith('.gz')):
self.reader = gzip.GzipFile(fileobj=self.reader)
self.aggro = aggressive
self.metadata = None
self.infos = None
self.filters = None
self.formats = None
self.samples = None
self._sample_indexes = None
self._header_lines = []
self._tabix = None
if aggressive:
self._mapper = self._none_map
else:
self._mapper = self._pass_map
self._parse_metainfo()
def __iter__(self):
return self
def _parse_metainfo(self):
'''Parse the information stored in the metainfo of the VCF.
The end user shouldn't have to use this. She can access the metainfo
directly with ``self.metadata``.'''
for attr in ('metadata', 'infos', 'filters', 'formats'):
setattr(self, attr, {})
parser = _vcf_metadata_parser()
line = self.reader.next()
while line.startswith('##'):
self._header_lines.append(line)
line = line.strip()
if line.startswith('##INFO'):
key, val = parser.read_info(line)
self.infos[key] = val
elif line.startswith('##FILTER'):
key, val = parser.read_filter(line)
self.filters[key] = val
elif line.startswith('##FORMAT'):
key, val = parser.read_format(line)
self.formats[key] = val
else:
key, val = parser.read_meta(line.strip())
self.metadata[key] = val
line = self.reader.next()
fields = line.split()
self.samples = fields[9:]
self._sample_indexes = dict([(x,i) for (i,x) in enumerate(self.samples)])
def _none_map(self, func, iterable, bad='.'):
'''``map``, but make bad values None.'''
return [func(x) if x != bad else None
for x in iterable]
def _pass_map(self, func, iterable, bad='.'):
'''``map``, but make bad values None.'''
return [func(x) if x != bad else bad
for x in iterable]
def _parse_info(self, info_str):
'''Parse the INFO field of a VCF entry into a dictionary of Python
types.
'''
entries = info_str.split(';')
retdict = {}
for entry in entries:
entry = entry.split('=')
ID = entry[0]
try:
entry_type = self.infos[ID].type
except KeyError:
try:
entry_type = RESERVED_INFO[ID]
except KeyError:
if entry[1:]:
entry_type = 'String'
else:
entry_type = 'Flag'
if entry_type == 'Integer':
vals = entry[1].split(',')
val = self._mapper(int, vals)
elif entry_type == 'Float':
vals = entry[1].split(',')
val = self._mapper(float, vals)
elif entry_type == 'Flag':
val = True
elif entry_type == 'String':
val = entry[1]
try:
if self.infos[ID].num == 1:
val = val[0]
except KeyError:
pass
retdict[ID] = val
return retdict
def _parse_samples(self, samples, samp_fmt, site):
'''Parse a sample entry according to the format specified in the FORMAT
column.'''
samp_data = []# OrderedDict()
samp_fmt = samp_fmt.split(':')
samp_fmt_types = []
for fmt in samp_fmt:
try:
entry_type = self.formats[fmt].type
except KeyError:
try:
entry_type = RESERVED_FORMAT[fmt]
except KeyError:
entry_type = 'String'
samp_fmt_types.append(entry_type)
for name, sample in itertools.izip(self.samples, samples):
sampdict = self._parse_sample(sample, samp_fmt, samp_fmt_types)
samp_data.append(_Call(site, name, sampdict))
return samp_data
def _parse_sample(self, sample, samp_fmt, samp_fmt_types):
mapper = self._mapper
sampdict = dict([(x, None) for x in samp_fmt])
for fmt, entry_type, vals in itertools.izip(samp_fmt, samp_fmt_types, sample.split(':')):
vals = vals.split(',')
if fmt == 'GT':
gt = vals[0]
if gt == './.':
if self.aggro:
gt = None
sampdict[fmt] = gt
break
else:
sampdict[fmt] = gt
else:
if entry_type == 'Integer':
sampdict[fmt] = mapper(int, vals)
elif entry_type == 'Float' or entry_type == 'Numeric':
sampdict[fmt] = mapper(float, vals)
else:
sampdict[fmt] = vals
return sampdict
def next(self):
'''Return the next record in the file.'''
row = self.reader.next().split()
chrom = row[0]
pos = int(row[1])
if row[2] != '.':
ID = row[2]
else:
ID = None if self.aggro else row[2]
ref = row[3]
alt = self._mapper(str, row[4].split(','))
if row[5] == '.':
qual = '.'
else:
qual = float(row[5]) if '.' in row[5] else int(row[5])
filt = row[6].split(';') if ';' in row[6] else row[6]
if filt == 'PASS' and self.aggro:
filt = None
info = self._parse_info(row[7])
try:
fmt = row[8]
except IndexError:
fmt = None
record = _Record(chrom, pos, ID, ref, alt, qual, filt, info, fmt, self._sample_indexes)
if fmt is not None:
samples = self._parse_samples(row[9:], fmt, record)
record.samples = samples
return record
def fetch(self, chrom, start, end):
if not pysam:
raise Exception('pysam not available, try "pip install pysam"?')
if not self.filename:
raise Exception('Please provide a filename (or a "normal" fsock)')
if not self._tabix:
self._tabix = pysam.Tabixfile(self.filename)
self.reader = self._tabix.fetch(chrom, start, end)
return self
class Writer(object):
fixed_fields = "#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT".split()
def __init__(self, stream, template):
self.writer = csv.writer(stream, delimiter="\t")
self.template = template
for line in template.metadata.items():
stream.write('##%s=%s\n' % line)
for line in template.infos.values():
stream.write('##INFO=<ID=%s,Number=%s,Type=%s,Description="%s">\n' % line)
for line in template.formats.values():
stream.write('##FORMAT=<ID=%s,Number=%s,Type=%s,Description="%s">\n' % line)
for line in template.filters.values():
stream.write('##FILTER=<ID=%s,Description="%s">\n' % line)
self.info_pattern = re.compile(r'''\#\#INFO=<
ID=(?P<id>[^,]+),
Number=(?P<number>-?\d+|\.|[AG]),
Type=(?P<type>Integer|Float|Flag|Character|String),
Description="(?P<desc>[^"]*)"
>''', re.VERBOSE)
self.filter_pattern = re.compile(r'''\#\#FILTER=<
ID=(?P<id>[^,]+),
Description="(?P<desc>[^"]*)"
>''', re.VERBOSE)
self.format_pattern = re.compile(r'''\#\#FORMAT=<
ID=(?P<id>.+),
Number=(?P<number>-?\d+|\.|[AG]),
Type=(?P<type>.+),
Description="(?P<desc>.*)"
>''', re.VERBOSE)
self.meta_pattern = re.compile(r'''##(?P<key>.+)=(?P<val>.+)''')
self.write_header()
def write_header(self):
# TODO: write INFO, etc
self.writer.writerow(self.fixed_fields + self.template.samples)
def write_record(self, record):
ffs = [record.CHROM, record.POS, record.ID, record.REF, self._format_alt(record.ALT),
record.QUAL, record.FILTER, self._format_info(record.INFO), record.FORMAT]
samples = [self._format_sample(record.FORMAT, sample)
for sample in record.samples]
self.writer.writerow(ffs + samples)
def _format_alt(self, alt):
return ','.join(alt)
def _format_info(self, info):
return ';'.join(["%s=%s" % (x, self._stringify(y)) for x, y in info.items()])
def _format_sample(self, fmt, sample):
if sample.data["GT"] == "./.":
return "./."
return ':'.join((str(self._stringify(sample.data[f])) for f in fmt.split(':')))
def _stringify(self, x):
if type(x) == type([]):
return ','.join(map(str, x))
return str(x)
class Filter(object):
name = 'filter'
description = 'VCF filter base class'
short_name = 'f'
@classmethod
def customize_parser(self):
pass
def __init__(self, args):
self.threshold = 0
def __call__(self):
raise NotImplementedError('Filters must implement this method')
def filter_name(self):
return '%s%s' % (self.short_name, self.threshold)
def __update_readme():
import sys
file('README.rst', 'w').write(sys.modules[__name__].__doc__)
# backwards compatibility
VCFReader = Reader
VCFWriter = Writer