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vcf.py
585 lines (482 loc) · 17.1 KB
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vcf.py
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#!/usr/bin/env python
import os
import re
import sys
import bz2
import gzip
import math
import argparse
import itertools
import logging as lg
import subprocess as sp
from peekorator import Peekorator
lg.basicConfig(level=lg.DEBUG)
nucleotides = ['A', 'C', 'G', 'T']
class SampleParseError(Exception):
pass
class SampleStats(object):
def __init__(self, format_def, format_string, sample_name):
self.format_def = format_def
self.format_string = format_string
self.sample = sample_name
self.fields = self.format_def.split(':')
self.values = self.format_string.split(':')
self._nf = []
self.info = {}
if format_string == '.':
pass
#no data
else:
self.interpret()
def interpret(self):
try:
assert(len(self.fields) == len(self.values))
except AssertionError:
lg.critical("parse problem '%s' - '%s'" % (self.fields, self.values))
raise SampleParseError()
for i, f in enumerate(self.fields):
if f == 'DP':
self.dp = int(self.values[i])
elif f == 'NF':
self._nf = map(int, self.values[i].split('|'))
else:
try:
self.info[f] = self.values[i]
self.__dict__[f] = self.values[i]
except:
print 'error'
print 'key', f
print 'val', self.values[i]
raise
def get_format_string(self):
newval = []
for i, fieldname in enumerate(self.fields):
if fieldname == 'DP':
newval.append(str(sum(self.nf)))
elif fieldname == 'NF':
newval.append("|".join(map(str, self.nf)))
else:
newval.append(self.values[i])
return ":".join(newval)
def set_nf(self, val):
self._nf = val
self.db = sum(val)
def get_nf(self):
return self._nf
nf = property(get_nf, set_nf)
def __str__(self):
return "".join(['A', 'C', 'G', 'T'][i]
for i,x
in enumerate(self.nf) if x)
def alleles(self):
return [['A', 'C', 'G', 'T'][i]
for i,x
in enumerate(self.nf) if x]
def get_major_allele(self, d=0.2):
"""
return the major allele - but only if there is a fractional
difference of d between the major & secondary allele
"""
alfs = [(x,i) for i,x in enumerate(self.allele_freqs())]
alfs.sort()
alfs.reverse()
lg.warning('%s' % self.seq_logo())
diff = alfs[0][0] - alfs[1][0]
if diff < d:
return None
else:
return ['A', 'C', 'G', 'T'][alfs[0][1]]
def allele_freqs(self):
if self.dp > 0:
rv = [(float(x) / self.dp) for x in self.nf]
else:
rv = [0.0, 0.0, 0.0, 0.0]
assert(max(rv) <= 1)
return rv
def allele_freqs_sort(self):
af = self.allele_freqs()
af.sort()
return af
def get_absolute_distance(self, other):
if str(self) != str(other):
return 1
else:
return 0
def get_euclidian_distance(self, other):
taf= self.allele_freqs()
oaf = other.allele_freqs()
squadiff = 0
for i in range(4):
squadiff += (taf[i] - oaf[i]) ** 2
return math.sqrt(squadiff)
def get_max_allelefreq_distance(self, other):
"""
Use the maximal allelefreq difference between self & other as
a distance measure
"""
return max([abs(x-y) for x,y in zip(self.allele_freqs(), other.allele_freqs())])
def no_alleles(self):
return len([x for x in self.nf if x > 0])
def seq_logo(self, logo_len=10, dottify='#'):
"""
Try to make a ascii seq logo
"""
if self.dp == 0:
return '-' + (' ' * (logo_len-1))
gt = [{True : 1, False: 0}[x>0] for x in self.nf]
ntleft = logo_len - sum(gt)
gtplus = [int(round( ntleft * (float(max(x,1)-1) / (self.dp-sum(gt)))))
for x in self.nf ]
gt = [sum(x) for x in zip(gt, gtplus)]
if sum(gt) < logo_len:
mx = gt.index(max(gt))
gt[mx] += (logo_len - sum(gt))
#assert(len(gt) == 4)
#assert(sum(gt) == logo_len)
if sum(gt) > logo_len:
mx = gt.index(max(gt))
gt[mx] -= (sum(gt) - logo_len)
logo = ('A' * gt[0]) + \
('C' * gt[1]) + \
('G' * gt[2]) + \
('T' * gt[3])
logo = logo.replace(dottify, '.')
return logo
class RefSampleStats(SampleStats):
def __init__(self, ref):
format_str = {
'a' : '50:50|00|00|00',
'c' : '50:00|50|00|00',
'g' : '50:00|00|50|00',
't' : '50:00|00|00|50',
'n' : '00:00|00|00|00'}.get(ref.lower(), '00:00|00|00|00')
super(RefSampleStats, self).__init__("DP:NF", format_str, "Reference")
class Locus(object):
def __init__(self, vcf_line, sample_names):
self.vcf_line = vcf_line
self.sample_names = sample_names
ls = self.vcf_line.split("\t")
self.ls = ls
self.seq = ls[0]
self.pos = int(ls[1])
self.snpid = ls[2]
self.ref = ls[3]
self.refStats = RefSampleStats(self.ref)
self.vars = ls[4].split(',')
self.score = float(ls[5])
self.filter = ls[6]
#parse info fields
self.info = {}
for i in ls[7].split(';'):
if not '=' in i:
k = i
v = True
else:
k,v = i.split('=', 1)
self.info[k] = v
if k == 'NS':
self.ns = int(v)
elif k == 'DP':
pass
#self._dp = int(v)
elif k == 'AN':
self.an = int(v)
#parse format fields
self.format_def = ls[8]
assert(len(ls[9:]) == len(self.sample_names))
self.samples = []
for i, format_string in enumerate(ls[9:]):
self.samples.append(SampleStats(self.format_def, format_string,
sample_name = self.sample_names[i]))
def set_dp(self, val):
pass
def get_dp(self):
return sum([sum(x.nf) for x in self.samples])
dp=property(get_dp, set_dp)
def simple(self):
"""
Return True if this locus has only one allele in all samples,
and if that allele corresponds to the reference genome
"""
for i in self.samples:
if str(i) != self.ref: return False
return True
def has_sample_variation(self, measure='absolute', maxval = 0, internal_only=True):
dm = self.dist_matrix(measure = measure)
#print 'x' * 80
#print self
#print dm
#get the submatrix that displays just the internal vaiation
#the leftmost column & bottom row show variation outer
im = [x[:-1] for x in dm[:-1]]
if measure=='absolute':
dist = sum([sum(x) for x in im])
#print 'ab', dist
elif measure=='allelefreq':
#print self.format_dist_matrix(range(len(im)), im)
dist = max([max(x) for x in im])
return dist > maxval
def format_dist_matrix(self, samples, matrix):
"""
Nicely format a dist matrix
"""
rv = ""
rv += "%20s" % ''
rv += " | ".join(["%10s" % x for x in samples])
rv += "\n"
for i, rw in enumerate(matrix):
rv += "%20s" % samples[i]
for j, cl in enumerate(rw):
if j > 0:
rv += " - "
if i <= j:
rv += "%10.4f" % cl
else:
rv += "%10s" % '*'
rv += "\n"
return rv
def dist_matrix(self, measure='absolute'):
nosamples = len(self.samples)
dm = [ [ 0 for x in range(nosamples+1)]
for x in range(nosamples+1) ]
for i in range(nosamples+1):
if i < nosamples:
s1 = self.samples[i]
else:
s1 = self.refStats
for j in range(nosamples + 1):
if j < nosamples:
s2 = self.samples[j]
else:
s2 = self.refStats
if i == j:
dm[i][j] = 0
if i > j:
continue
if measure == 'absolute':
dm[i][j] = s1.get_absolute_distance(s2)
if measure == 'euclidian':
dm[i][j] = s1.get_euclidian_distance(s2)
if measure == 'allelefreq':
dm[i][j] = s1.get_max_allelefreq_distance(s2)
return dm
def build_vcf_line(self):
ivals = []
for k in self.info.keys():
if k == 'DP':
ivals.append(self.dp)
elif k == 'AN':
ivals.append(self.an)
else:
ivals.append(self.info[k])
infostr = ';'.join(
[ '%s=%s' % (k,v) for (k,v) in zip(self.info.keys(), ivals)])
groupstr = "\t".join([x.get_format_string() for x in self.samples])
return "\t".join(
map(str,
[ self.seq,
self.pos,
self.snpid,
self.ref,
','.join(self.vars),
self.score,
self.filter,
infostr,
self.format_def,
groupstr
]))
def min_depth(self):
return min([x.dp for x in self.samples])
def max_no_alleles(self):
return max([x.no_alleles() for x in self.samples])
def min_no_alleles(self):
return min([x.no_alleles() for x in self.samples])
def nice_str(self, t='genotype', sep="\t"):
if t == 'genotype':
return sep.join(
map(str, [
self.seq, self.pos, self.ref, self.dp]
+ self.samples
))
elif t == 'nuccount':
return sep.join(
map(str, [
self.seq, self.pos, self.ref, self.dp] +
[sep.join(["%5d" % d for d in x.nf])for x in self.samples]
))
elif t == 'allfreq':
return sep.join(
map(str, [
self.seq, self.pos, self.ref, self.dp] +
[sep.join(["%5d" % int(d*100) for d in x.allele_freqs_sort()])
for x in self.samples]
))
elif t[:8] == 'logoplus':
logo_len = int(t[8:])
return sep.join(
map(str,
[ self.seq, self.pos, self.ref, self.dp] +
[x.seq_logo(logo_len=logo_len, dottify=self.ref)
for x in self.samples] +
[ 'ACGT' ] +
["|".join(["%2d" % d for d in x.nf])for x in self.samples]
))
elif t[:4] == 'logo':
logo_len = int(t[4:])
return sep.join(
map(str,
[ self.seq, self.pos, self.ref, self.dp] +
[x.seq_logo(logo_len=logo_len, dottify=self.ref)
for x in self.samples]
))
def __str__(self):
return "%-20s %6d %2s - %s" % (
self.seq, self.pos, self.ref,
" ".join(["%4s" % x for x in self.samples])
)
class PSVCF(object):
def __init__(self, filename, region=None):
self.filename = filename
self.region = False
self.region_str = region
self.region_has_pos = False
self.been_in_region = False
self.lg = lg.getLogger('PSVCF')
if region:
self.region = True
_x = self.region_str.split(':')
self.region_seq = _x[0]
if len(_x) > 1:
self.region_has_pos = True
_y = _x[1].split('-')
self.region_start = int(_y[0])
self.region_end = int(_y[1])
self.file_mode = 'file'
if filename == '-':
self.file_mode = 'stdin'
self.F = Peekorator(sys.stdin)
elif filename[-3:] == '.gz' and os.path.exists(filename + '.tbi') \
and self.region:
self.lg.debug('tabix mode')
self.file_mode = 'tabix'
#TABIX mode!
cl = 'tabix -h %s %s' % (filename, self.region_str)
self.lg.debug("running tabis: %s" % cl)
self.TABIX_PROCESS = sp.Popen(cl.split(), stdout=sp.PIPE)
self.F = Peekorator(self.TABIX_PROCESS.stdout)
elif filename[-3:] == '.gz':
self.lg.debug('Opening as bz2')
self.F = Peekorator(gzip.open(self.filename))
elif filename[-4:] == '.bz2':
self.lg.debug('Opening as bz2')
self.F = Peekorator(bz2.BZ2File(self.filename))
else:
self.lg.debug('normal file mode')
self.F = Peekorator(open(self.filename))
self.meta_header_lines = []
self.header_line = ""
#read header
while True:
line = self.F.peek
if not line:
raise StopIteration
elif not line.strip():
self.F.next()
pass
elif line[:2] == '##':
self.F.next()
self.meta_header_lines.append(line.strip())
elif line[:6] == '#CHROM':
#header:
self.interpret_header(line)
break
elif line[0] != '#':
#bummer - no header??
self.create_dummy_header()
break
self.lg.info('Opening %s' % self.filename)
def __iter__(self):
return self
def create_dummy_header(self):
self.header_line = "\t".join(
['#CHROM', 'POS', 'ID', 'REF', 'ALT', 'QUAL', 'FILTER', 'INFO', 'FORMAT', 'sample'])
ls = self.header_line.split("\t")
self.sample_names = ls[9:]
def interpret_header(self, line):
self.header_line = line.strip()
ls = self.header_line.split("\t")
assert(ls[:9] == ['#CHROM', 'POS', 'ID', 'REF', 'ALT', 'QUAL', 'FILTER', 'INFO', 'FORMAT'])
self.sample_names = ls[9:]
def simple_names(self):
"""
Return simplified sample names
"""
def _simple_name(s):
s = os.path.basename(s)
s = s.replace('.vcf', '')
s = s.replace('.bam', '')
s = s.replace('.bz2', '')
return s
return [_simple_name(x) for x in self.sample_names]
def next(self):
while True:
line = self.F.next()
if not line:
#EOF
raise StopIteration
line = line.strip()
if not line:
#empty line
continue
if line[:2] == '##':
self.meta_header_lines.append(line.strip())
continue
if line[:6] == '#CHROM':
#header:
self.interpret_header(line)
continue
try:
loc = Locus(line, sample_names = self.sample_names)
except SampleParseError:
lg.critical("could not parse line")
lg.critical(line)
raise SampleParseError()
if not self.region:
#No region is specified - return regardless
return loc
#figure out if this locus falls within the specified region
if loc.seq != self.region_seq:
if self.been_in_region:
self.fin()
if not self.region_has_pos:
self.been_in_region = True
return loc
if loc.pos < self.region_start:
continue
if loc.pos > self.region_end:
raise StopIteration
self.been_in_region = True
return loc
def fin():
"""
Finish iterations
"""
if self.file_mode == 'file':
self.F.close()
elif self.file_mode == 'stdin':
pass
elif self.file_mode == 'tabix':
self.F.close()
raise StopIteration
def add_meta(self, k, v):
"""
Set a meta key/value pair - will be added to the header
"""
self.meta_header_lines.append("##%s=%s" % (k,v))
def build_header(self):
"""
Return a new header
"""
rv = self.meta_header_lines
rv.append(self.header_line)
return "\n".join(rv) + "\n"