def main(argv):
options = launch_options.Options(argv, bin_home, truspades_home)
support.ensure_dir_existence(options.output_dir)
log = create_log(options)
dataset_file = os.path.join(options.output_dir, "dataset.info")
if options.continue_launch:
dataset = barcode_extraction.ReadDataset(dataset_file, log)
elif options.input_dirs is not None:
dataset = generate_dataset(options.input_dirs, log)
if dataset is None:
log.info("Error: could not parse dataset from input directories\n")
sys.exit(1)
barcode_extraction.print_dataset(dataset, dataset_file, log)
log.info("Dataset generated. See result in " + dataset_file)
else:
dataset = barcode_extraction.ReadDataset(options.dataset_file, log)
barcode_extraction.print_dataset(dataset, dataset_file, log)
log_dir = os.path.join(options.output_dir, "logs")
support.ensure_dir_existence(log_dir)
# if options.print_commands:
# verify_exists(options.output_dir)
# print_commands(commands, options)
if options.mode == "run_truspades":
RunTruSPAdes(dataset, log_dir, options, log)
elif options.mode == "construct_subreferences":
reference_construction.ConstructSubreferences(
dataset, options.reference, options.output_dir, options.index, options.threads, log=None
)
log.info("TruSPAdes launch successfully finished")
if options.test:
CheckTestSuccess(options, log)
def ConstructSubreferences(datasets, reference_file, output_dir, index = None, threads = 1, log = None):
bwa_command = "bin/spades-bwa"
if log == None:
log = logging.getLogger('reference_construction')
log.setLevel(logging.INFO)
console = logging.StreamHandler(sys.stderr)
console.setFormatter(logging.Formatter('%(message)s'))
console.setLevel(logging.INFO)
log.addHandler(console)
support.ensure_dir_existence(output_dir)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
if index == None:
log.info("Constructing index\n")
index = alignment.index_bwa(bwa_command, log, reference_file, os.path.join(output_dir, "bwa_index"), "bwtsw")
sam_dir = os.path.join(output_dir, "alignments")
log.info("Aligning barcodes\n")
sam_files = AlignToReference(datasets, sam_dir, bwa_command, log, index, threads)
subreference_dir = os.path.join(output_dir, "subreferences")
filtered_dir = os.path.join(output_dir, "filtered")
support.recreate_dir(subreference_dir)
support.recreate_dir(filtered_dir)
log.info("Constructing subreferences")
subreferences_list = [(barcode_id, ConstructSubreferenceFromSam(barcode_sam)) for barcode_id, barcode_sam in sam_files]
log.info("Reading reference")
reference = ReadReference(reference_file)
log.info("Printing output")
PrintAll([(barcode, filtered) for barcode, (filtered, subreference) in subreferences_list], reference, filtered_dir)
PrintAll([(barcode, subreference) for barcode, (filtered, subreference) in subreferences_list], reference, subreference_dir)
log.info("Subreference construction finished. See results in " + output_dir)
def RunTruQuast(input_dir, reference_dir, output_dir, threads):
support.ensure_dir_existence(output_dir)
if os.path.exists(os.path.join(input_dir, "dataset.info")):
ids = [
barcode.id for barcode in barcode_extraction.ReadDataset(
os.path.join(input_dir, "dataset.info"))
]
files = [
os.path.join(input_dir, "barcodes", bid, "truseq_long_reads.fasta")
for bid in ids
]
else:
files = [
os.path.join(input_dir, file) for file in os.listdir(input_dir)
if file.endswith(".fasta") or file.endswith(".fa")
]
ids = [
f[:f.rfind(".")] for f in os.listdir(input_dir)
if file.endswith(".fasta") or file.endswith(".fa")
]
barcode_quast_dir = os.path.join(output_dir, "barcode_quast")
RunBarcodeQuast(zip(ids, files), barcode_quast_dir, reference_dir, threads)
names, reports = ParseResults(barcode_quast_dir, ids)
names.append("#partially unaligned")
values = CollectResults(names, reports)
results = open(os.path.join(output_dir, "results.tsv"), "w")
for name in names:
results.write(name + "\t" + str(int(values[name])) + "\t" +
str(values[name] / len(ids)) + "\n")
results.close()
def main(argv):
options = launch_options.Options(argv, spades_home, truspades_home, spades_version)
support.ensure_dir_existence(options.output_dir)
if options.test and not options.continue_launch:
support.recreate_dir(options.output_dir)
log = create_log(options)
dataset_file = os.path.join(options.output_dir, "dataset.info")
if options.continue_launch:
dataset = barcode_extraction.ReadDataset(dataset_file, log)
elif options.input_dirs is not None:
dataset = generate_dataset(options.input_dirs, log)
if dataset is None:
log.info("Error: could not parse dataset from input directories\n")
sys.exit(1)
barcode_extraction.print_dataset(dataset, dataset_file, log)
log.info("Dataset generated. See result in " + dataset_file)
else:
dataset = barcode_extraction.ReadDataset(options.dataset_file, log)
barcode_extraction.print_dataset(dataset, dataset_file, log)
log_dir = os.path.join(options.output_dir, "logs")
support.ensure_dir_existence(log_dir)
# if options.print_commands:
# verify_exists(options.output_dir)
# print_commands(commands, options)
if options.mode == "run_truspades":
RunTruSPAdes(dataset, log_dir, options, log)
elif options.mode == "construct_subreferences":
reference_construction.ConstructSubreferences(dataset, options.reference, options.output_dir, options.index, options.threads, log = None)
log.info("TruSPAdes launch successfully finished")
if options.test:
CheckTestSuccess(options, log)
def RunTruSPAdes(dataset, log_dir, options, log):
log.info("Launching truSPAdes assembly in " + str(options.threads) +
" threads")
log.info("You can find logs for separate barcodes in " + log_dir)
barcodes_dir = os.path.join(options.output_dir, "barcodes")
support.ensure_dir_existence(barcodes_dir)
commands = [(barcode.id,
command_line(barcode, barcodes_dir, options.spades_options,
options.continue_launch)) for barcode in dataset]
task = parallel_launcher.ExternalCallTask(os.path.join(log_dir, "{0}.log"),
"", log.name)
errors = parallel_launcher.run_in_parallel(task, commands, options.threads)
if errors != 0:
log.info(str(errors) + " barcodes failed to assemble")
check_results(dataset, barcodes_dir, log)
output_base = os.path.join(options.output_dir, "TSLR")
collect_contigs(dataset, barcodes_dir, output_base, "fasta")
collect_contigs(dataset, barcodes_dir, output_base, "fastq")
log.info("Assembled virtual long TruSeq reads can be found in " +
os.path.join(options.output_dir, "TSLR.fasta"))
if options.clean:
SaveContigs(barcodes_dir, dataset, "fasta")
SaveContigs(barcodes_dir, dataset, "fastq")
for barcode in dataset:
shutil.rmtree(os.path.join(barcodes_dir, barcode.id))
def ConstructSubreferences(datasets, reference_file, output_dir, index = None, threads = 1, log = None):
bwa_command = "bin/bwa-spades"
if log == None:
log = logging.getLogger('reference_construction')
log.setLevel(logging.INFO)
console = logging.StreamHandler(sys.stderr)
console.setFormatter(logging.Formatter('%(message)s'))
console.setLevel(logging.INFO)
log.addHandler(console)
support.ensure_dir_existence(output_dir)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
if index == None:
log.info("Constructing index\n")
index = alignment.index_bwa(bwa_command, log, reference_file, os.path.join(output_dir, "bwa_index"), "bwtsw")
sam_dir = os.path.join(output_dir, "alignments")
log.info("Aligning barcodes\n")
sam_files = AlignToReference(datasets, sam_dir, bwa_command, log, index, threads)
subreference_dir = os.path.join(output_dir, "subreferences")
filtered_dir = os.path.join(output_dir, "filtered")
support.recreate_dir(subreference_dir)
support.recreate_dir(filtered_dir)
log.info("Constructing subreferences")
subreferences_list = [(barcode_id, ConstructSubreferenceFromSam(barcode_sam)) for barcode_id, barcode_sam in sam_files]
log.info("Reading reference")
reference = ReadReference(reference_file)
log.info("Printing output")
PrintAll([(barcode, filtered) for barcode, (filtered, subreference) in subreferences_list], reference, filtered_dir)
PrintAll([(barcode, subreference) for barcode, (filtered, subreference) in subreferences_list], reference, subreference_dir)
log.info("Subreference construction finished. See results in " + output_dir)
def SaveContigs(barcodes_dir, dataset, format):
contig_dir = os.path.join(barcodes_dir, format)
support.ensure_dir_existence(contig_dir)
for barcode in dataset:
if os.path.isfile(
os.path.join(barcodes_dir, barcode.id,
"truseq_long_reads." + format)):
shutil.copyfileobj(
open(
os.path.join(barcodes_dir, barcode.id,
"truseq_long_reads." + format), "rb"),
gzip.open(
os.path.join(contig_dir,
barcode.id + "." + format + ".gz"), "wb"))
def RunTruSPAdes(dataset, log_dir, options, log):
log.info("Launching truSPAdes assembly in " + str(options.threads) + " threads")
log.info("You can find logs for separate barcodes in " + log_dir)
barcodes_dir = os.path.join(options.output_dir, "barcodes")
support.ensure_dir_existence(barcodes_dir)
commands = [
(barcode.id, command_line(barcode, barcodes_dir, options.spades_options, options.continue_launch))
for barcode in dataset
]
task = parallel_launcher.ExternalCallTask(os.path.join(log_dir, "{0}.log"), "", log.name)
errors = parallel_launcher.run_in_parallel(task, commands, options.threads)
if errors != 0:
log.info(str(errors) + " barcodes failed to assemble")
check_results(dataset, barcodes_dir, log)
output_base = os.path.join(options.output_dir, "TSLR")
collect_contigs(dataset, barcodes_dir, output_base, "fasta")
collect_contigs(dataset, barcodes_dir, output_base, "fastq")
log.info("Assembled virtual long TruSeq reads can be found in " + os.path.join(options.output_dir, "TSLR.fasta"))
def test_args():
'''
Put default args for test case.
'''
global options_storage
import tempfile
options_storage.output_dir = tempfile.mkdtemp("gadma_test_dir")
options_storage.output_dir = support.ensure_dir_existence(
options_storage.output_dir)
options_storage.input_file = os.path.join(support.get_home_dir(), "..",
"fs_examples", "test.fs")
options_storage.input_data, options_storage.ns, options_storage.pop_labels = support.load_spectrum(
options_storage.input_file, None, None)
options_storage.ns = np.array(options_storage.ns)
options_storage.number_of_populations = 1
options_storage.linked_snp = False
options_storage.theta = 0.37976
options_storage.gen_time = 25
options_storage.initial_structure = np.array([1])
options_storage.final_structure = np.array([2])
options_storage.size_of_generation = 5
options_storage.fracs = [
float(x) for x in options_storage.fracs.split(",")
]
options_storage.frac_of_old_models = options_storage.fracs[0]
options_storage.frac_of_mutated_models = options_storage.fracs[1]
options_storage.frac_of_crossed_models = options_storage.fracs[2]
options_storage.optimize_name = 'hill_climbing'
options_storage.moments_scenario = True
options_storage.relative_params = False
options_storage.dadi_pts = [20, 30, 40]
options_storage.repeats = 2
options_storage.processes = 2
options_storage.epsilon = 1
options_storage.test = True
options_storage.multinom = True
options_storage.final_check()
return options_storage
def check(self):
'''
Check correctness of parameters. Unless throws error.
'''
if self.multinom is None:
if self.model_func_file is None:
self.multinom = False
else:
self.multinom = True
if self.pop_labels is not None:
self.pop_labels = [x.strip() for x in self.pop_labels.split(',')]
if self.ns is not None:
self.ns = support.check_comma_sep_list(self.ns)
self.input_file = support.check_file_existence(self.input_file)
if self.resume_dir is not None:
self.resume_dir = support.check_dir_existence(self.resume_dir)
if self.resume_dir is not None and self.output_dir is None:
self.output_dir = support.ensure_dir_existence(
self.resume_dir + "_resumed", check_emptiness=True)
elif self.output_dir is None:
support.error("Parameter `Output directory` is required")
else:
self.output_dir = support.ensure_dir_existence(
self.output_dir, check_emptiness=True)
if self.input_file is None:
support.error(
"Parameter `Input file` is required")
if self.theta is None:
support.warning(
"`Theta0` is not specified. It would be 1.0.")
if self.gen_time is None:
support.warning(
"`Time for one generation` is not specified. Time will be in genetic units.")
self.input_data, self.ns, self.pop_labels = support.load_spectrum(
self.input_file, self.ns, self.pop_labels)
self.ns = np.array(self.ns)
self.number_of_populations = len(self.ns)
# Linked or unlinked data
if not self.linked_snp and self.boot_dir is not None:
support.warning(
"SNP's are marked as unlinked, so the directory with bootstrap will be ignored.")
elif self.linked_snp:
if self.boot_dir is not None:
self.boot_dir = support.check_dir_existence(self.boot_dir)
self.boots = gadma.Inference.load_bootstrap_data_from_dir(self.boot_dir, self.ns, self.pop_labels)
# Custom model
if self.model_func_file is not None:
self.model_func_file = support.check_file_existence(self.model_func_file)
file_with_model_func = imp.load_source('module', self.model_func_file)
try:
self.model_func = file_with_model_func.model_func
except:
support.error(
"File " + self.model_func_file + ' does not contain function named `model_func`.')
if self.model_func_file is not None:
if self.p_ids is not None:
self.p_ids = support.check_comma_sep_list(self.p_ids, is_int=False)
self.fracs = [float(x) for x in self.fracs.split(",")]
if len(self.fracs) != 3:
support.error(
"length of `Fractions` (Parameters of genetic algorithm) must be 3")
self.frac_of_old_models = self.fracs[0]
self.frac_of_mutated_models = self.fracs[1]
self.frac_of_crossed_models = self.fracs[2]
if self.moments_scenario and self.dadi_pts is not None:
support.warning(
"Moments doesn't use --pts argument, so it would be ignored")
if self.dadi_pts is None:
max_n = max(self.ns)
self.dadi_pts = [max_n, max_n + 10, max_n + 20]
else:
self.dadi_pts = support.check_comma_sep_list(self.dadi_pts)
self.put_default_structures()
self.final_check()
def SaveContigs(barcodes_dir, dataset, format):
contig_dir = os.path.join(barcodes_dir, format)
support.ensure_dir_existence(contig_dir)
for barcode in dataset:
if os.path.isfile(os.path.join(barcodes_dir, barcode.id, "truseq_long_reads." + format)):
shutil.copyfileobj(open(os.path.join(barcodes_dir, barcode.id, "truseq_long_reads." + format), "rb"), gzip.open(os.path.join(contig_dir, barcode.id + "." + format + ".gz"), "wb"))
