def tb_parse_mapping_frag(self, genome_seq, enzyme_name, window1_full,
window1_frag, window2_full, window2_frag, reads):
"""
Function to map the aligned reads and return the matching pairs
Parameters
----------
genome_seq : dict
Object containing the sequence of each of the chromosomes
enzyme_name : str
Name of the enzyme used to digest the genome
window1_full : str
Location of the first window index file
window1_frag : str
Location of the second window index file
window2_full : str
Location of the first window index file
window2_frag : str
Location of the second window index file
reads : str
Location of the reads thats that has a matching location at both
ends of the paired reads
Returns
-------
reads : str
Location of the intersection of mapped reads that have matching
reads in both pair end files
"""
print("TB WINDOWS - full 1", window1_full)
print("TB WINDOWS - frag 1", window1_frag)
print("TB WINDOWS - full 2", window2_full)
print("TB WINDOWS - frag 2", window2_frag)
# root_name = reads.split("/")
# reads1 = "/".join(root_name) + '/reads_1.tsv'
# reads2 = "/".join(root_name) + '/reads_2.tsv'
reads1 = reads + '_reads_1.tsv'
reads2 = reads + '_reads_2.tsv'
reads_both = reads + '_reads_both.tsv'
parse_map([window1_frag, window1_full], [window2_frag, window2_full],
out_file1=reads1,
out_file2=reads2,
genome_seq=genome_seq,
re_name=enzyme_name,
verbose=True)
get_intersection(reads1, reads2, reads_both, verbose=True)
with open(reads, "wb") as f_out:
with open(reads_both, "rb") as f_in:
f_out.write(f_in.read())
return True
def main():
fastq = '/scratch/db/FASTQs/hsap/dixon_2012/dixon-2012_200bp.fastq'
fastq = 'short_dixon-2012_200bp.fastq'
# fastq = '/scratch/test/sample_dataset/FASTQs/sample_hsap_HindIII.fastq'
gem_index_path = '/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.gem'
out_map_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read1/'
out_map_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read2/'
temp_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp1/'
temp_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp2/'
print 'read 1'
outfiles1 = full_mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
temp_dir=temp_dir1, windows=((1,100),), add_site=True)
print 'read 2'
outfiles2 = full_mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
temp_dir=temp_dir2, windows=((101, 200),), add_site=True)
# print 'read 1'
# outfiles1 = mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
# temp_dir=temp_dir1,
# windows=(zip(*([0] * len(range(25, 105, 5)),
# range(25,105,5)))))
# print 'read 2'
# outfiles2 = mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
# temp_dir=temp_dir2,
# windows=(zip(*([100] * len(range(125, 205, 5)),
# range(125,205,5)))))
print outfiles1
print 'xcmvnkljnv'
print outfiles2
from pytadbit.parsers.map_parser import parse_map
from pytadbit.parsers.genome_parser import parse_fasta
from pytadbit.mapping.mapper import get_intersection
from pytadbit.mapping.filter import filter_reads, apply_filter
read1, read2 = 'read1.tsv', 'read2.tsv',
parse_map(outfiles1, outfiles2, out_file1=read1, out_file2=read2,
genome_seq=parse_fasta('/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.fa'),
re_name='HindIII', verbose=True)
reads = 'both_reads.tsv'
get_intersection(read1, read2, reads)
masked = filter_reads(reads)
freads = 'filtered_reads.tsv'
apply_filter(reads, freads, masked)
def main():
fastq = '/scratch/db/FASTQs/hsap/dixon_2012/dixon-2012_200bp.fastq'
fastq = 'short_dixon-2012_200bp.fastq'
# fastq = '/scratch/test/sample_dataset/FASTQs/sample_hsap_HindIII.fastq'
gem_index_path = '/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.gem'
out_map_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read1/'
out_map_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read2/'
temp_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp1/'
temp_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp2/'
print 'read 1'
outfiles1 = full_mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
temp_dir=temp_dir1, windows=((1,100),), add_site=True)
print 'read 2'
outfiles2 = full_mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
temp_dir=temp_dir2, windows=((101, 200),), add_site=True)
# print 'read 1'
# outfiles1 = mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
# temp_dir=temp_dir1,
# windows=(zip(*([0] * len(range(25, 105, 5)),
# range(25,105,5)))))
# print 'read 2'
# outfiles2 = mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
# temp_dir=temp_dir2,
# windows=(zip(*([100] * len(range(125, 205, 5)),
# range(125,205,5)))))
print outfiles1
print 'xcmvnkljnv'
print outfiles2
from pytadbit.parsers.map_parser import parse_map
from pytadbit.parsers.genome_parser import parse_fasta
from pytadbit.mapping.mapper import get_intersection
from pytadbit.mapping.filter import filter_reads, apply_filter
read1, read2 = 'read1.tsv', 'read2.tsv',
parse_map(outfiles1, outfiles2, out_file1=read1, out_file2=read2,
genome_seq=parse_fasta('/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.fa'),
re_name='HindIII', verbose=True)
reads = 'both_reads.tsv'
get_intersection(read1, read2, reads)
masked = filter_reads(reads)
freads = 'filtered_reads.tsv'
apply_filter(reads, freads, masked)
def parseMaps(self, num_cpus=8):
"""
Merge the 2 read maps together
Requires 8 CPU
"""
# new file with info of each "read1" and its placement with respect to RE sites
reads1 = self.parsed_reads_dir + '/read1.tsv'
# new file with info of each "read2" and its placement with respect to RE sites
reads2 = self.parsed_reads_dir + '/read2.tsv'
mapped_rN = self.getMappedWindows()
print 'Parse MAP files...'
parse_map(mapped_rN["mapped_r1"],
mapped_rN["mapped_r2"],
out_file1=reads1,
out_file2=reads2,
genome_seq=self.genome_seq,
re_name=self.enzyme_name,
verbose=True,
ncpus=num_cpus)
def run(opts):
check_options(opts)
launch_time = time.localtime()
reads = [1] if opts.read == 1 else [2] if opts.read == 2 else [1, 2]
if not opts.mapped1 and not opts.mapped2:
f_names1, f_names2, renz = load_parameters_fromdb(
opts, reads, opts.jobids)
else:
if opts.mapped1:
f_names1 = opts.mapped1
if opts.mapped2:
f_names2 = opts.mapped2
renz = opts.renz
renz = renz.split('-')
opts.workdir = path.abspath(opts.workdir)
name = path.split(opts.workdir)[-1]
param_hash = digest_parameters(opts)
outdir = '02_parsed_reads'
mkdir(path.join(opts.workdir, outdir))
if not opts.read:
out_file1 = path.join(opts.workdir, outdir,
'%s_r1_%s.tsv' % (name, param_hash))
out_file2 = path.join(opts.workdir, outdir,
'%s_r2_%s.tsv' % (name, param_hash))
elif opts.read == 1:
out_file1 = path.join(opts.workdir, outdir,
'%s_r1_%s.tsv' % (name, param_hash))
out_file2 = None
f_names2 = None
elif opts.read == 2:
out_file2 = None
f_names1 = f_names2
f_names2 = None
out_file1 = path.join(opts.workdir, outdir,
'%s_r2_%s.tsv' % (name, param_hash))
logging.info('parsing genomic sequence')
try:
# allows the use of pickle genome to make it faster
genome = load(open(opts.genome[0], 'rb'))
except (UnpicklingError, KeyError):
genome = parse_fasta(opts.genome, chr_regexp=opts.filter_chrom)
if not opts.skip:
logging.info('parsing reads in %s project', name)
if opts.mapped1 or opts.mapped2:
counts, multis = parse_sam(f_names1,
f_names2,
out_file1=out_file1,
out_file2=out_file2,
re_name=renz,
verbose=True,
genome_seq=genome,
compress=opts.compress_input)
else:
counts, multis = parse_map(f_names1,
f_names2,
out_file1=out_file1,
out_file2=out_file2,
re_name=renz,
verbose=True,
genome_seq=genome,
compress=opts.compress_input)
else:
counts = {}
counts[0] = {}
fhandler = open(out_file1)
for line in fhandler:
if line.startswith('# MAPPED '):
_, _, item, value = line.split()
counts[0][item] = int(value)
elif not line.startswith('#'):
break
multis = {}
multis[0] = {}
for line in fhandler:
if '|||' in line:
try:
multis[0][line.count('|||')] += 1
except KeyError:
multis[0][line.count('|||')] = 1
if out_file2:
counts[1] = {}
fhandler = open(out_file2)
for line in fhandler:
if line.startswith('# MAPPED '):
_, _, item, value = line.split()
counts[1][item] = int(value)
elif not line.startswith('#'):
break
multis[1] = 0
for line in fhandler:
if '|||' in line:
multis[1] += line.count('|||')
# write machine log
while path.exists(path.join(opts.workdir, '__lock_log')):
time.sleep(0.5)
open(path.join(opts.workdir, '__lock_log'), 'a').close()
with open(path.join(opts.workdir, 'trace.log'), "a") as mlog:
for read in counts:
for item in counts[read]:
mlog.write('# PARSED READ%s PATH\t%d\t%s\n' %
(read, counts[read][item],
out_file1 if read == 1 else out_file2))
# release lock
try:
remove(path.join(opts.workdir, '__lock_log'))
except OSError:
pass
finish_time = time.localtime()
# save all job information to sqlite DB
save_to_db(opts, counts, multis, f_names1, f_names2, out_file1, out_file2,
launch_time, finish_time)
def run(opts):
check_options(opts)
launch_time = time.localtime()
reads = [1] if opts.read == 1 else [2] if opts.read == 2 else [1, 2]
f_names1, f_names2, renz = load_parameters_fromdb(opts, reads, opts.jobids)
renz = renz.split('-')
opts.workdir = path.abspath(opts.workdir)
name = path.split(opts.workdir)[-1]
param_hash = digest_parameters(opts)
outdir = '02_parsed_reads'
mkdir(path.join(opts.workdir, outdir))
if not opts.read:
out_file1 = path.join(opts.workdir, outdir, '%s_r1_%s.tsv' % (name, param_hash))
out_file2 = path.join(opts.workdir, outdir, '%s_r2_%s.tsv' % (name, param_hash))
elif opts.read == 1:
out_file1 = path.join(opts.workdir, outdir, '%s_r1_%s.tsv' % (name, param_hash))
out_file2 = None
f_names2 = None
elif opts.read == 2:
out_file2 = None
f_names1 = f_names2
f_names2 = None
out_file1 = path.join(opts.workdir, outdir, '%s_r2_%s.tsv' % (name, param_hash))
logging.info('parsing genomic sequence')
try:
# allows the use of cPickle genome to make it faster
genome = load(open(opts.genome[0]))
except UnpicklingError:
genome = parse_fasta(opts.genome, chr_regexp=opts.filter_chrom)
if not opts.skip:
logging.info('parsing reads in %s project', name)
counts, multis = parse_map(f_names1, f_names2, out_file1=out_file1,
out_file2=out_file2, re_name=renz, verbose=True,
genome_seq=genome, compress=opts.compress_input)
else:
counts = {}
counts[0] = {}
fhandler = open(out_file1)
for line in fhandler:
if line.startswith('# MAPPED '):
_, _, item, value = line.split()
counts[0][item] = int(value)
elif not line.startswith('#'):
break
multis = {}
multis[0] = {}
for line in fhandler:
if '|||' in line:
try:
multis[0][line.count('|||')] += 1
except KeyError:
multis[0][line.count('|||')] = 1
if out_file2:
counts[1] = {}
fhandler = open(out_file2)
for line in fhandler:
if line.startswith('# MAPPED '):
_, _, item, value = line.split()
counts[1][item] = int(value)
elif not line.startswith('#'):
break
multis[1] = 0
for line in fhandler:
if '|||' in line:
multis[1] += line.count('|||')
# write machine log
while path.exists(path.join(opts.workdir, '__lock_log')):
time.sleep(0.5)
open(path.join(opts.workdir, '__lock_log'), 'a').close()
with open(path.join(opts.workdir, 'trace.log'), "a") as mlog:
for read in counts:
for item in counts[read]:
mlog.write('# PARSED READ%s PATH\t%d\t%s\n' % (
read, counts[read][item],
out_file1 if read == 1 else out_file2))
# release lock
try:
remove(path.join(opts.workdir, '__lock_log'))
except OSError:
pass
finish_time = time.localtime()
# save all job information to sqlite DB
save_to_db(opts, counts, multis, f_names1, f_names2, out_file1, out_file2,
launch_time, finish_time)
from pytadbit.parsers.map_parser import parse_map
from pytadbit.parsers.genome_parser import parse_fasta
from pytadbit.mapping import get_intersection
# Load the genome
genome_seq = parse_fasta(fasta)
# Output directory
RESULTS = '%s/results/%s/processed_reads' % (SAMPLE, version)
if not os.path.exists(RESULTS):
os.makedirs(RESULTS)
infiles = []
outfiles = []
for infile in [paired1, paired2]:
bname = infile.split("/")[-1].replace(".fastq.gz", "")
maps = glob.glob('%s/%s/*' % (MAP_DIR, bname))
infiles.append(maps)
outfiles.append('%s/%s_map.tsv' % (RESULTS, bname))
parse_map(infiles[0],
infiles[1],
outfiles[0],
outfiles[1],
genome_seq,
restriction_enzyme,
verbose=True,
ncpus=slots)
final_output = outfiles[0].replace('read1', 'both')
get_intersection(outfiles[0], outfiles[1], final_output, verbose=True)
def tb_parse_mapping_iter(self, genome_seq, enzyme_name, window1_1,
window1_2, window1_3, window1_4, window2_1,
window2_2, window2_3, window2_4, reads):
"""
Function to map the aligned reads and return the matching pairs
Parameters
----------
genome_seq : dict
Object containing the sequence of each of the chromosomes
enzyme_name : str
Name of the enzyme used to digest the genome
window1_1 : str
Location of the first window index file
window1_2 : str
Location of the second window index file
window1_3 : str
Location of the third window index file
window1_4 : str
Location of the fourth window index file
window2_1 : str
Location of the first window index file
window2_2 : str
Location of the second window index file
window2_3 : str
Location of the third window index file
window2_4 : str
Location of the fourth window index file
reads : str
Location of the reads thats that has a matching location at both
ends of the paired reads
Returns
-------
reads : str
Location of the intersection of mapped reads that have matching
reads in both pair end files
"""
reads1 = reads + '_reads_1.tsv'
reads2 = reads + '_reads_2.tsv'
reads_both = reads + '_reads_both.tsv'
parse_map(
[window1_1, window1_2, window1_3, window1_4],
[window2_1, window2_2, window2_3, window2_4],
out_file1=reads1,
out_file2=reads2,
genome_seq=genome_seq,
re_name=enzyme_name,
verbose=True,
# ncpus=32
)
get_intersection(reads1, reads2, reads_both, verbose=True)
with open(reads, "wb") as f_out:
with open(reads_both, "rb") as f_in:
f_out.write(f_in.read())
return True
def run(opts):
check_options(opts)
launch_time = time.localtime()
reads = [1] if opts.read == 1 else [2] if opts.read == 2 else [1, 2]
f_names1, f_names2, renz = load_parameters_fromdb(opts.workdir, reads, opts.jobids)
name = path.split(opts.workdir)[-1]
param_hash = digest_parameters(opts)
outdir = '02_parsed_reads'
mkdir(path.join(opts.workdir, outdir))
if not opts.read:
out_file1 = path.join(opts.workdir, outdir, '%s_r1_%s.tsv' % (name, param_hash))
out_file2 = path.join(opts.workdir, outdir, '%s_r2_%s.tsv' % (name, param_hash))
elif opts.read == 1:
out_file1 = path.join(opts.workdir, outdir, '%s_r1_%s.tsv' % (name, param_hash))
out_file2 = None
f_names2 = None
elif opts.read == 2:
out_file2 = None
f_names1 = f_names2
f_names2 = None
out_file1 = path.join(opts.workdir, outdir, '%s_r2_%s.tsv' % (name, param_hash))
logging.info('parsing genomic sequence')
try:
# allows the use of cPickle genome to make it faster
genome = load(open(opts.genome[0]))
except UnpicklingError:
genome = parse_fasta(opts.genome)
if not opts.skip:
logging.info('parsing reads in %s project', name)
counts, multis = parse_map(f_names1, f_names2, out_file1=out_file1,
out_file2=out_file2, re_name=renz, verbose=True,
genome_seq=genome, compress=opts.compress_input)
else:
counts = {}
counts[0] = {}
fhandler = open(out_file1)
for line in fhandler:
if line.startswith('# MAPPED '):
_, _, item, value = line.split()
counts[0][item] = int(value)
elif not line.startswith('#'):
break
multis = {}
multis[0] = 0
for line in fhandler:
if '|||' in line:
multis[0] += line.count('|||')
if out_file2:
counts[1] = {}
fhandler = open(out_file2)
for line in fhandler:
if line.startswith('# MAPPED '):
_, _, item, value = line.split()
counts[1][item] = int(value)
elif not line.startswith('#'):
break
multis[1] = 0
for line in fhandler:
if '|||' in line:
multis[1] += line.count('|||')
# write machine log
with open(path.join(opts.workdir, 'trace.log'), "a") as mlog:
fcntl.flock(mlog, fcntl.LOCK_EX)
for read in counts:
for item in counts[read]:
mlog.write('# PARSED READ%s PATH\t%d\t%s\n' % (
read, counts[read][item],
out_file1 if read == 1 else out_file2))
fcntl.flock(mlog, fcntl.LOCK_UN)
finish_time = time.localtime()
# save all job information to sqlite DB
save_to_db(opts, counts, multis, f_names1, f_names2, out_file1, out_file2,
launch_time, finish_time)
