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snATAC.ct2bin.py
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snATAC.ct2bin.py
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#!/usr/bin/env python
# count reads to bins with cell barcode
import argparse
parser = argparse.ArgumentParser(description='count reads to bins with bin/cell coordinate')
parser.add_argument('-i', type=str, dest="input", help='input bam file')
parser.add_argument('-g', '--genomeSize', type=str, dest="genomeSize", help='genome size')
parser.add_argument('-b', '--binSize', type=int, dest="binSize", default=5000, help='bin size')
parser.add_argument('-o', type=str, dest="output", help='output prefix')
args = parser.parse_args()
import sys
import pysam
import copy
import numpy as np
from collections import Counter
import pybedtools
from time import perf_counter as pc
from scipy import sparse
from scipy.sparse import save_npz
def is_sorted_queryname(header):
"""
Check if bam fiel is sorted by read name.
"""
if("HD" in header):
if("SO" in header["HD"]):
if(header["HD"]["SO"] == "queryname"):
return True
return False
def bins_maker(genomeSize, bin_size):
genomeSizes = pybedtools.BedTool(genomeSize)
bins = genomeSizes.window_maker(g=genomeSize, w=bin_size)
bin_dict = {}
idx = 0
for i in bins:
chr = i.chrom
start = i.start
end = i.end
key = (chr+"\t"+str(start)+"\t"+str(end))
bin_dict[key] = idx
idx += 1
return bin_dict
def get_genSize(headerSQ):
genSize = {}
for i in range(len(headerSQ)):
key, values = headerSQ[i]["SN"], headerSQ[i]["LN"]
genSize[key]= values
return genSize
def main():
bamf = args.input
bin_size = int(args.binSize)
genomeSize = args.genomeSize
outf = args.output
start_time = pc()
# start reading the bam
samfile = pysam.AlignmentFile(bamf, "rb")
# check if bam file is sorted by name or not
if not is_sorted_queryname(samfile.header):
sys.exit("Error: bam needs to be sorted by read name")
# get chormosome size from header
headerSQ = samfile.header["SQ"]
genSizes = get_genSize(headerSQ)
bins_dict = bins_maker(genomeSize, bin_size)
idx = 0
counts = {}
barcodes = {}
barcode_tmp = "AAA"
n_lines = 0
while True:
try:
read1 = next(samfile)
read2 = next(samfile)
except: # to the end
break
n_lines += 1
if n_lines% 1000000 == 0 :
print( "%s read pairs processed."%n_lines)
if read1.is_proper_pair:
if read1.is_read1:
pass
else:
tmp = copy.deepcopy(read1)
read1 = read2
read2 = tmp
ref1 = read1.reference_name
ref2 = read2.reference_name
barcode = read1.qname.strip().split(":")[0]
if barcode not in barcodes:
barcodes[barcode] = idx
idx += 1
length = read1.reference_length
if not read1.is_reverse:
pos = read1.reference_start
else:
pos = read2.reference_start
chrSize1 = int(genSizes[ref1])
chrSize2 = int(genSizes[ref2])
if(ref1 == ref2 and abs(read1.reference_start//bin_size - read1.next_reference_start//bin_size) <= 1):
if (pos//bin_size + 1) * bin_size < chrSize1:
key = (ref1+"\t"+str((pos//bin_size) * bin_size)+"\t"+str((pos//bin_size + 1) * bin_size)+"\t"+read1.qname+"\t"+"."+"\t"+"+"+"\t"+barcode)
if key in counts:
counts[key] += 1
else:
counts[key] = 1
else:
key = (ref1+"\t"+str((pos//bin_size) * bin_size)+"\t"+str(chrSize1)+"\t"+read1.qname+"\t"+"."+"\t"+"+"+"\t"+barcode)
if key in counts:
counts[key] += 1
else:
counts[key] = 1
if(ref1 == ref2 and abs(read1.reference_start//bin_size - read1.next_reference_start//bin_size) > 1):
midpos = pos + length * 0.5
if (midpos//bin_size + 1) * bin_size < chrSize1:
key = (ref1+"\t"+str((midpos//bin_size) * bin_size)+"\t"+str((midpos//bin_size + 1) * bin_size)+"\t"+read1.qname+"\t"+"."+"\t"+"+"+"\t"+barcode)
if key in counts:
counts[key] += 1
else:
counts[key] = 1
else:
key = (ref1+"\t"+str((midpos//bin_size) * bin_size)+"\t"+str(chrSize1)+"\t"+read1.qname+"\t"+"."+"\t"+"+"+"\t"+barcode)
if key in counts:
counts[key] += 1
else:
counts[key] = 1
samfile.close()
outbed = ".".join([outf,"bed"])
outmat = ".".join([outf,"mat"])
outxgi = ".".join([outf,"xgi"])
outygi = ".".join([outf,"ygi"])
outnpz = ".".join([outf,"npz"])
with open(outxgi, 'w') as outxgi:
for key, val in barcodes.items():
outxgi.write(key + "\n")
outxgi.close()
with open(outygi, 'w') as outygi:
for key, val in bins_dict.items():
outygi.write(key + "\n")
outygi.close()
with open(outbed, 'w') as outbed:
for key,val in counts.items():
outbed.write(str(key) + "\t" + str(val) + "\n")
outbed.close()
with open(outmat, 'w') as outmat:
xgi = []
ygi = []
ct = []
for key,val in counts.items():
items = key.strip().split("\t")
xgi_key = items[3]
ygi_key = items[0]+"\t"+items[1]+"\t"+items[2]
xgi_idx = barcodes[xgi_key]
ygi_idx = bins_dict[ygi_key]
outmat.write(str(xgi_idx) + "\t" + str(ygi_idx) + "\t" + str(val) + "\n")
xgi.append(xgi_idx)
ygi.append(ygi_idx)
ct.append(val)
cooMx = sparse.coo_matrix((ct,(xgi,ygi)))
save_npz(outnpz, cooMx)
outmat.close()
end_time = pc()
print('Used (secs): ', end_time - start_time)
if __name__ == "__main__":
main()