def __init__(self, chromosome_name, bam_file_path, draft_file_path, truth_bam, hp_tag, train_mode):
"""
Initialize a manager object
:param chromosome_name: Name of the chromosome
:param bam_file_path: Path to the BAM file
:param draft_file_path: Path to the reference FASTA file
:param truth_bam: Path to the truth sequence to reference mapping file
"""
# --- initialize handlers ---
# create objects to handle different files and query
self.bam_path = bam_file_path
self.fasta_path = draft_file_path
self.bam_handler = PEPPER_HP.BAM_handler(bam_file_path)
self.fasta_handler = PEPPER_HP.FASTA_handler(draft_file_path)
self.train_mode = train_mode
self.hp_tag = hp_tag
self.downsample_rate = 1.0
self.truth_bam = None
if self.train_mode:
self.truth_bam = truth_bam
# --- initialize names ---
# name of the chromosome
self.chromosome_name = chromosome_name
def __init__(self, reference_file_path, contigs, sample_name, output_dir,
filename):
self.fasta_handler = PEPPER_HP.FASTA_handler(reference_file_path)
self.contigs = contigs
vcf_header = self.get_vcf_header(sample_name, contigs)
self.vcf_file = VariantFile(output_dir + filename + '.vcf',
'w',
header=vcf_header)
def __init__(self, vcf1, vcf2, ref_fasta, only_overlapping=True, discard_phase=False, detailed_info=False):
"""Initialize variant merging.
Merge variants from two haploid VCFs into a diploid vcf. Variants in
one file which overlap with variants in the other will have their alts
padded.
.. warning::
Variants in a single vcf file should not overlap with each other.
:param vcf1, vcf2: paths to haploid vcf files.
:param ref_fasta: path to reference.fasta file.
:param only_overlapping: bool, merge only overlapping variants (not
adjacent ones).
:param discard_phase: bool, if False, preserve phase, else output
unphased variants.
"""
self.only_overlapping = only_overlapping
self.discard_phase = discard_phase
self.detailed_info = detailed_info
self.vcfs = [VCFReader(vcf) for vcf in (vcf1, vcf2)]
for vcf in self.vcfs:
vcf.index() # create tree
self.fasta = pysam.FastaFile(ref_fasta)
all_contigs = list(set(itertools.chain(*[v.chroms for v in self.vcfs])))
all_contigs = sorted(all_contigs, key=natural_key)
fasta_handler = PEPPER_HP.FASTA_handler(ref_fasta)
sqs = fasta_handler.get_chromosome_names()
self.chroms = []
for sq in sqs:
if sq not in all_contigs:
continue
sq_id = sq
ln = fasta_handler.get_chromosome_sequence_length(sq)
self.chroms.append((sq_id, ln))
def get_chromosome_list(chromosome_names, ref_file, bam_file, region_bed):
"""
PARSES THROUGH THE CHROMOSOME PARAMETER TO FIND OUT WHICH REGIONS TO PROCESS
:param chromosome_names: NAME OF CHROMOSOME
:param ref_file: PATH TO THE REFERENCE FILE
:param bam_file: PATH TO BAM FILE
:return: LIST OF CHROMOSOME IN REGION SPECIFIC FORMAT
"""
if not chromosome_names and not region_bed:
fasta_handler = PEPPER_HP.FASTA_handler(ref_file)
bam_handler = PEPPER_HP.BAM_handler(bam_file)
bam_contigs = bam_handler.get_chromosome_sequence_names()
fasta_contigs = fasta_handler.get_chromosome_names()
common_contigs = list(set(fasta_contigs) & set(bam_contigs))
common_contigs = list(set(common_contigs) - set(EXCLUDED_HUMAN_CONTIGS))
if len(common_contigs) == 0:
sys.stderr.write("[" + datetime.now().strftime('%m-%d-%Y %H:%M:%S') + "] "
+ "ERROR: NO COMMON CONTIGS FOUND BETWEEN THE BAM FILE AND THE FASTA FILE.")
sys.stderr.flush()
exit(1)
common_contigs = sorted(common_contigs, key=UserInterfaceSupport.natural_key)
sys.stderr.write("[" + datetime.now().strftime('%m-%d-%Y %H:%M:%S') + "] INFO: COMMON CONTIGS FOUND: " + str(common_contigs) + "\n")
sys.stderr.flush()
chromosome_name_list = []
for contig_name in common_contigs:
chromosome_name_list.append((contig_name, None))
return chromosome_name_list
if region_bed:
chromosome_name_list = []
with open(region_bed) as fp:
line = fp.readline()
cnt = 1
while line:
line_to_list = line.rstrip().split('\t')
chr_name, start_pos, end_pos = line_to_list[0], int(line_to_list[1]), int(line_to_list[2])
region = sorted([start_pos, end_pos])
chromosome_name_list.append((chr_name, region))
line = fp.readline()
cnt += 1
return chromosome_name_list
split_names = chromosome_names.strip().split(',')
split_names = [name.strip() for name in split_names]
chromosome_name_list = []
for name in split_names:
# split on region
region = None
if ':' in name:
name_region = name.strip().split(':')
if len(name_region) != 2:
sys.stderr.write("ERROR: --region INVALID value.\n")
exit(0)
name, region = tuple(name_region)
region = region.strip().split('-')
region = [int(pos) for pos in region]
if len(region) != 2 or not region[0] <= region[1]:
sys.stderr.write("ERROR: --region INVALID value.\n")
exit(0)
range_split = name.split('-')
if len(range_split) > 1:
chr_prefix = ''
for p in name:
if p.isdigit():
break
else:
chr_prefix = chr_prefix + p
int_ranges = []
for item in range_split:
s = ''.join(i for i in item if i.isdigit())
int_ranges.append(int(s))
int_ranges = sorted(int_ranges)
for chr_seq in range(int_ranges[0], int_ranges[-1] + 1):
chromosome_name_list.append((chr_prefix + str(chr_seq), region))
else:
chromosome_name_list.append((name, region))
return chromosome_name_list
def chromosome_level_parallelization(chr_list,
bam_file,
draft_file,
truth_bam,
hp_tag,
output_path,
total_threads,
train_mode,
realignment_flag):
if train_mode:
max_size = 10000
else:
max_size = 10000
start_time = time.time()
fasta_handler = PEPPER_HP.FASTA_handler(draft_file)
all_intervals = []
# first calculate all the intervals that we need to process
for chr_name, region in chr_list:
# contig update message
if not region:
interval_start, interval_end = (0, fasta_handler.get_chromosome_sequence_length(chr_name) - 1)
else:
interval_start, interval_end = tuple(region)
interval_start = max(0, interval_start)
interval_end = min(interval_end, fasta_handler.get_chromosome_sequence_length(chr_name) - 1)
# this is the interval size each of the process is going to get which is 10^6
# I will split this into 10^4 size inside the worker process
for pos in range(interval_start, interval_end, max_size):
pos_start = max(interval_start, pos - ImageSizeOptions.MIN_IMAGE_OVERLAP)
pos_end = min(interval_end, pos + max_size + ImageSizeOptions.MIN_IMAGE_OVERLAP)
all_intervals.append((chr_name, pos_start, pos_end))
# all intervals calculated now
# contig update message
sys.stderr.write("[" + datetime.now().strftime('%m-%d-%Y %H:%M:%S') + "] "
+ "INFO: TOTAL CONTIGS: " + str(len(chr_list))
+ " TOTAL INTERVALS: " + str(len(all_intervals)) + "\n")
sys.stderr.flush()
args = (output_path, bam_file, draft_file, truth_bam, hp_tag, train_mode, realignment_flag)
with concurrent.futures.ProcessPoolExecutor(max_workers=total_threads) as executor:
futures = [executor.submit(UserInterfaceSupport.image_generator, args, all_intervals, total_threads,
thread_id)
for thread_id in range(0, total_threads)]
for fut in concurrent.futures.as_completed(futures):
if fut.exception() is None:
# get the results
thread_id = fut.result()
sys.stderr.write("[" + str(datetime.now().strftime('%m-%d-%Y %H:%M:%S')) + "] INFO: THREAD "
+ str(thread_id) + " FINISHED SUCCESSFULLY.\n")
else:
sys.stderr.write("ERROR: " + str(fut.exception()) + "\n")
fut._result = None # python issue 27144
end_time = time.time()
mins = int((end_time - start_time) / 60)
secs = int((end_time - start_time)) % 60
sys.stderr.write("[" + str(datetime.now().strftime('%m-%d-%Y %H:%M:%S')) + "] INFO: FINISHED IMAGE GENERATION\n")
sys.stderr.write("[" + str(datetime.now().strftime('%m-%d-%Y %H:%M:%S')) + "] INFO: ELAPSED TIME: " + str(mins) + " Min " + str(secs) + " Sec\n")