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hisat2_extract_snps_haplotypes_UCSC.py
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hisat2_extract_snps_haplotypes_UCSC.py
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#!/usr/bin/env python
#
# Copyright 2015, Daehwan Kim <infphilo@gmail.com>
#
# This file is part of HISAT 2.
#
# HISAT 2 is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# HISAT 2 is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with HISAT 2. If not, see <http://www.gnu.org/licenses/>.
#
import sys, subprocess
import re
from argparse import ArgumentParser, FileType
"""
"""
def reverse_complement(seq):
result = ""
for nt in seq:
base = nt
if nt == 'A':
base = 'T'
elif nt == 'a':
base = 't'
elif nt == 'C':
base = 'G'
elif nt == 'c':
base = 'g'
elif nt == 'G':
base = 'C'
elif nt == 'g':
base = 'c'
elif nt == 'T':
base = 'A'
elif nt == 't':
base = 'a'
result = base + result
return result
"""
"""
def read_genome(genome_file):
chr_dic = {}
chr_name, sequence = "", ""
for line in genome_file:
if line.startswith(">"):
if chr_name and sequence:
chr_dic[chr_name] = sequence
chr_name = line.strip().split()[0][1:]
sequence = ""
else:
sequence += line.strip()
if chr_name and sequence:
chr_dic[chr_name] = sequence
return chr_dic
"""
Compare two variants [chr, pos, type, data, dic]
"""
def compare_vars(a, b):
a_chr, a_pos, a_type, a_data = a[:4]
b_chr, b_pos, b_type, b_data = b[:4]
# daehwan - for debugging purposes
if a_chr != b_chr:
print a
print b
assert a_chr == b_chr
if a_pos != b_pos:
return a_pos - b_pos
if a_type != b_type:
if a_type == 'I':
return -1
elif b_type == 'I':
return 1
if a_type == 'S':
return -1
else:
return 1
if a_data < b_data:
return -1
elif a_data > b_data:
return 1
else:
return 0
"""
"""
def compatible_vars(a, b):
a_chr, a_pos, a_type, a_data = a[:4]
b_chr, b_pos, b_type, b_data = b[:4]
assert a_chr == b_chr
assert a_pos <= b_pos
if a_pos == b_pos:
return False
if a_type == 'D':
if b_pos <= a_pos + a_data:
return False
return True
"""
"""
def generate_haplotypes(snp_file,
haplotype_file,
vars,
inter_gap,
intra_gap,
num_haplotypes):
assert len(vars) > 0
# Sort variants and remove redundant variants
vars = sorted(vars, cmp=compare_vars)
tmp_vars = []
v = 0
while v < len(vars):
var = vars[v]
for v2 in range(v + 1, len(vars)):
var2 = vars[v2]
if compare_vars(var, var2) == 0:
v += 1
else:
assert compare_vars(var, var2) < 0
break
tmp_vars.append(var)
v += 1
vars = tmp_vars
# Create new variant ID for variants with the same ID
# e.g. same two variant ID, rs60160543, are split into rs60160543.0 and rs60160543.1
vars_count = {}
for var in vars:
id = var[4]["id"]
if id not in vars_count:
vars_count[id] = 0
vars_count[id] += 1
vars_duplicate = set()
for id, count in vars_count.items():
if count <= 1:
continue
vars_duplicate.add(id)
vars_count = {}
for var in vars:
id = var[4]["id"]
if id not in vars_count:
vars_count[id] = 0
else:
vars_count[id] += 1
if id not in vars_duplicate:
var[4]["id2"] = id
else:
var[4]["id2"] = "%s.%d" % (id, vars_count[id])
# variant compatibility
vars_cmpt = [-1 for i in range(len(vars))]
for v in range(len(vars)):
var_chr, var_pos, var_type, var_data = vars[v][:4]
if var_type == 'D':
var_pos += (var_data - 1)
for v2 in range(v + 1, len(vars)):
if vars_cmpt[v2] >= 0:
continue
var2_chr, var2_pos = vars[v2][:2]
if var_chr != var2_chr:
break
if var_pos + inter_gap < var2_pos:
break
vars_cmpt[v2] = v
# Assign genotypes for those missing genotypes
genotypes_list = []
for v in range(len(vars)):
var = vars[v]
var_dic = var[4]
freq = var_dic["freq"]
used = [False for i in range(100)]
if vars_cmpt[v] >= 0:
v2 = v - 1
while v2 >= vars_cmpt[v]:
var2 = vars[v2]
if not compatible_vars(var2, var) or \
freq >= 0.1:
var2_dic = var2[4]
assert "genotype" in var2_dic
genotype_num = var2_dic["genotype"]
used[genotype_num] = True
v2 -= 1
assert False in used
for i in range(len(used)):
if not used[i]:
var_dic["genotype"] = i
break
genotypes_list.append(var_dic["genotype"])
# Write SNPs into a file (.snp)
for var in vars:
chr, pos, type, data, var_dic = var
varID = var_dic["id2"]
if type == 'S':
type = "single"
elif type == 'D':
type = "deletion"
else:
assert type == 'I'
type = "insertion"
print >> snp_file, "%s\t%s\t%s\t%s\t%s" % \
(varID, type, chr, pos, data)
# genotypes_list looks like
# Var0: 0
# Var1: 0
# Var2: 1
# Var3: 2
# Get haplotypes from genotypes_list
max_genotype_num = max(genotypes_list)
haplotypes = ["" for i in range(max_genotype_num + 1)]
for i in range(len(genotypes_list)):
num = genotypes_list[i]
if haplotypes[num] == "":
haplotypes[num] = str(i)
else:
haplotypes[num] += ("#%d" % i)
haplotypes = set(haplotypes)
# haplotypes look like
# '8#10#12#23', '8#12#23', '5#8#12#23#30'
# Split some haplotypes that include large gaps inside
def split_haplotypes(haplotypes):
split_haplotypes = set()
for haplotype in haplotypes:
haplotype = haplotype.split('#')
assert len(haplotype) > 0
if len(haplotype) == 1:
split_haplotypes.add(haplotype[0])
continue
prev_s, s = 0, 1
while s < len(haplotype):
_, prev_locus, prev_type, prev_data, _ = vars[int(haplotype[s-1])]
_, locus, type, data, _ = vars[int(haplotype[s])]
prev_locus, locus = int(prev_locus), int(locus)
if prev_type == 'D':
prev_locus += (int(prev_data) - 1)
if prev_locus + intra_gap < locus:
split_haplotypes.add('#'.join(haplotype[prev_s:s]))
prev_s = s
s += 1
if s == len(haplotype):
split_haplotypes.add('#'.join(haplotype[prev_s:s]))
return split_haplotypes
haplotypes2 = split_haplotypes(haplotypes)
def cmp_haplotype(a, b):
a = a.split('#')
_, a1_locus, _, _, _ = vars[int(a[0])]
_, a2_locus, a2_type, a2_data, _ = vars[int(a[-1])]
a_begin, a_end = int(a1_locus), int(a2_locus)
if a2_type == 'D':
a_end += (int(a2_data) - 1)
b = b.split('#')
_, b1_locus, _, _, _ = vars[int(b[0])]
_, b2_locus, b2_type, b2_data, _ = vars[int(b[-1])]
b_begin, b_end = int(b1_locus), int(b2_locus)
if b2_type == 'D':
b_end += (int(b2_data) - 1)
if a_begin != b_begin:
return a_begin - b_begin
return a_end - b_end
haplotypes = sorted(list(haplotypes2), cmp=cmp_haplotype)
# Write haplotypes
for h_i in range(len(haplotypes)):
h = haplotypes[h_i].split('#')
chr, h1_locus, _, _, _ = vars[int(h[0])]
_, h2_locus, h2_type, h2_data, _ = vars[int(h[-1])]
h_begin, h_end = int(h1_locus), int(h2_locus)
if h2_type == 'D':
h_end += (int(h2_data) - 1)
assert h_begin <= h_end
h_new_begin = h_begin
for h_j in reversed(range(0, h_i)):
hc = haplotypes[h_j].split('#')
_, hc_begin, hc_type, hc_data, _ = vars[int(hc[-1])]
hc_begin = int(hc_begin)
hc_end = hc_begin
if hc_type == 'D':
hc_end += (int(hc_data) - 1)
if hc_end + inter_gap < h_begin:
break
if h_new_begin > hc_end:
h_new_begin = hc_end
assert h_new_begin <= h_begin
h_add = []
for id in h:
var_dic = vars[int(id)][4]
h_add.append(var_dic["id2"])
print >> haplotype_file, "ht%d\t%s\t%d\t%d\t%s" % \
(num_haplotypes, chr, h_new_begin, h_end, ','.join(h_add))
num_haplotypes += 1
return num_haplotypes
"""
"""
def main(genome_file,
snp_fname,
base_fname,
inter_gap,
intra_gap,
verbose,
testset):
# load genomic sequences
chr_dic = read_genome(genome_file)
if testset:
ref_testset_file = open(base_fname + ".ref.testset.fa", "w")
alt_testset_file = open(base_fname + ".alt.testset.fa", "w")
snp_out_file = open(base_fname + ".snp", 'w')
haplotype_out_file = open(base_fname + ".haplotype", 'w')
# load SNPs
snp_list = []
prev_chr, curr_right = "", -1
num_haplotypes = 0
if snp_fname.endswith(".gz"):
snp_cmd = ["gzip", "-cd", snp_fname]
else:
snp_cmd = ["cat", snp_fname]
snp_proc = subprocess.Popen(snp_cmd,
stdout=subprocess.PIPE,
stderr=open("/dev/null", 'w'))
ids_seen = set()
for line in snp_proc.stdout:
if not line or line.startswith('#'):
continue
line = line.strip()
try:
fields = line.split('\t')
"""
id, chr, start, end, rs_id, score, strand, refNCBI, refUCSC, observed, molType, classType, valid, \
avHet, avHetSE, func, locType, weight, exceptions, submitterCount, submitters, \
alleleFreqCount, alleles, alleleNs, alleleFreqs, bitfields = fields
"""
id, chr, start, end, rs_id, score, strand, refNCBI, refUCSC, observed, molType, classType = fields[:12]
alleleFreqs = fields[-2].split(',')[:-1]
if len(alleleFreqs) > 0:
try:
float(alleleFreqs[0])
except ValueError:
alleleFreqs = []
except ValueError:
continue
start, end = int(start), int(end)
score = int(score)
if molType != "genomic":
continue
if classType not in ["single", "deletion", "insertion"]:
continue
if classType == "single":
if start + 1 != end:
continue
elif classType == "deletion":
assert start < end
else:
assert classType == "insertion"
if start != end:
continue
if chr not in chr_dic:
continue
chr_seq = chr_dic[chr]
chr_len = len(chr_seq)
if start >= len(chr_seq):
continue
if rs_id in ids_seen:
continue
ids_seen.add(rs_id)
if (prev_chr != chr or curr_right + inter_gap < start) and \
len(snp_list) > 0:
num_haplotypes = generate_haplotypes(snp_out_file,
haplotype_out_file,
snp_list,
inter_gap,
intra_gap,
num_haplotypes)
snp_list = []
observed = observed.upper()
allele_list = observed.split("/")
if len(alleleFreqs) == 0:
alleleFreqs = [0.0 for i in range(len(allele_list))]
# Reverse complement alleles if strand is negative
if strand == "-":
tmp_allele_list = []
for allele in allele_list:
tmp_allele_list.append(reverse_complement(allele))
allele_list = tmp_allele_list
if classType == "single":
allele_count = min(len(allele_list), len(alleleFreqs))
ref_base = chr_seq[start].upper()
if ref_base not in allele_list:
continue
for a in range(allele_count):
allele = allele_list[a]
freq = float(alleleFreqs[a])
if allele not in "ACGT" or len(allele) != 1:
continue
if allele == ref_base:
continue
snp_list.append([chr, start, 'S', allele, {"id":rs_id, "freq":freq}])
if testset:
ref_seq = chr_seq[start-50:start+50]
alt_seq = chr_seq[start-50:start] + allele + chr_seq[start+1:start+50]
print >> ref_testset_file, ">%s_single_%d" % (rs_id, start - 50)
print >> ref_testset_file, ref_seq
print >> alt_testset_file, ">%s_single_%d_%s" % (rs_id, start - 50, ref_seq)
print >> alt_testset_file, alt_seq
elif classType == "deletion":
if start > 0:
prev_base = chr_seq[start-1].upper()
if prev_base not in "ACGT":
continue
if len(allele_list) != 2 or \
len(allele_list) != len(alleleFreqs):
continue
freq = 0.0
if allele_list[0] == "-":
freq = float(alleleFreqs[1])
else:
if allele_list[1] != "-":
continue
freq = float(alleleFreqs[0])
delLen = end - start
snp_list.append([chr, start, 'D', delLen, {"id":rs_id, "freq":freq}])
if testset and delLen > 0 and delLen <= 10:
ref_seq = chr_seq[start-50:start+50]
alt_seq = chr_seq[start-50:start] + chr_seq[start+delLen:start+50+delLen]
print >> ref_testset_file, ">%s_deletion_%d" % (rs_id, start - 50)
print >> ref_testset_file, ref_seq
print >> alt_testset_file, ">%s_deletion_%d_%s" % (rs_id, start - 50, ref_seq)
print >> alt_testset_file, alt_seq
else:
assert classType == "insertion"
if start > 0:
prev_base = chr_seq[start-1].upper()
if prev_base not in "ACGT":
continue
allele_count = min(len(allele_list), len(alleleFreqs))
for a in range(allele_count):
allele = allele_list[a]
freq = float(alleleFreqs[a])
if allele == "-" or len(allele) <= 0:
continue
if re.match('^[ACGT]+$', allele):
snp_list.append([chr, start, 'I', allele, {"id":rs_id, "freq":freq}])
insLen = len(allele)
if testset and insLen > 0 and insLen <= 10:
ref_seq = chr_seq[start-50:start+50]
alt_seq = chr_seq[start-50:start] + allele + chr_seq[start:start+50-insLen]
print >> ref_testset_file, ">%s_insertion_%d" % (rs_id, start - 50)
print >> ref_testset_file, ref_seq
print >> alt_testset_file, ">%s_insertion_%d_%s" % (rs_id, start - 50, ref_seq)
print >> alt_testset_file, alt_seq
if curr_right < end:
curr_right = end
if prev_chr != chr:
curr_right = end
prev_chr = chr
if testset:
ref_testset_file.close()
alt_testset_file.close()
if len(snp_list) > 0:
generate_haplotypes(snp_out_file,
haplotype_out_file,
snp_list,
inter_gap,
intra_gap,
num_haplotypes)
snp_list = []
snp_out_file.close()
haplotype_out_file.close()
if __name__ == '__main__':
parser = ArgumentParser(
description='Extract SNPs and haplotypes from a SNP file downloaded from UCSC (e.g. http://hgdownload.soe.ucsc.edu/goldenPath/hg38/database/snp144.txt.gz)')
parser.add_argument('genome_file',
nargs='?',
type=FileType('r'),
help='input genome file (e.g. genome.fa)')
parser.add_argument('snp_fname',
nargs='?',
type=str,
help='input snp file downloaded from UCSC (plain text or gzipped file is accepted: snp144Common.txt or snp144Common.txt.gz)')
parser.add_argument("base_fname",
nargs='?',
type=str,
help="base filename for SNPs and haplotypes")
parser.add_argument("--inter-gap",
dest="inter_gap",
type=int,
default=30,
help="Maximum distance for variants to be in the same haplotype")
parser.add_argument("--intra-gap",
dest="intra_gap",
type=int,
default=50,
help="Break a haplotype into several haplotypes")
parser.add_argument('-v', '--verbose',
dest='verbose',
action='store_true',
help='also print some statistics to stderr')
parser.add_argument('--testset',
dest='testset',
action='store_true',
help='print test reads')
args = parser.parse_args()
if not args.genome_file or \
not args.snp_fname or \
not args.base_fname:
parser.print_help()
exit(1)
main(args.genome_file,
args.snp_fname,
args.base_fname,
args.inter_gap,
args.intra_gap,
args.verbose,
args.testset)