def open(self):
make_directory(self.trace_dir)
self.alpha_writer = ConcentrationParameterWriter(self.trace_dir)
self.labels_writer = LabelsWriter(self.trace_dir, self.mutation_ids)
self.cellular_frequency_writers = {}
for sample_id in self.sample_ids:
self.cellular_frequency_writers[sample_id] = CellularFrequenciesWriter(self.trace_dir,
sample_id,
self.mutation_ids)
if self.update_precision:
self.precision_writer = PrecisionWriter(self.trace_dir)
def open(self):
make_directory(self.trace_dir)
self.alpha_writer = ConcentrationParameterWriter(self.trace_dir)
self.labels_writer = LabelsWriter(self.trace_dir, self.mutation_ids)
self.cellular_frequency_writers = {}
for sample_id in self.sample_ids:
self.cellular_frequency_writers[
sample_id] = CellularFrequenciesWriter(self.trace_dir,
sample_id,
self.mutation_ids)
if self.update_precision:
self.precision_writer = PrecisionWriter(self.trace_dir)
def _setup_analysis(config_extras_file, density, in_files, init_method,
num_iters, samples, prior, tumour_contents, working_dir):
make_directory(working_dir)
make_directory(os.path.join(working_dir, 'yaml'))
mutations_files = OrderedDict()
_tumour_contents = {}
for i, in_file in enumerate(in_files):
if samples is not None:
sample_id = samples[i]
else:
sample_id = os.path.splitext(os.path.basename(in_file))[0]
mutations_files[sample_id] = os.path.join(working_dir, 'yaml',
'{0}.yaml'.format(sample_id))
_build_mutations_file(in_file, mutations_files[sample_id], prior)
if tumour_contents is not None:
_tumour_contents[sample_id] = tumour_contents[i]
else:
_tumour_contents[sample_id] = 1.0
config_file = os.path.join(working_dir, 'config.yaml')
_write_config_file(
config_file=config_file,
density=density,
init_method=init_method,
mutations_files=mutations_files,
num_iters=num_iters,
tumour_contents=_tumour_contents,
working_dir=working_dir,
config_extras_file=config_extras_file,
)
return config_file
def open(self):
make_directory(paths.get_trace_dir(self.config_file))
self.alpha_writer = ConcentrationParameterWriter(paths.get_concentration_trace_file(self.config_file))
self.labels_writer = LabelsWriter(
paths.get_labels_trace_file(self.config_file),
self.mutation_ids
)
self.cellular_frequency_writers = {}
for sample_id, file_name in paths.get_cellular_prevalence_trace_files(self.config_file).items():
self.cellular_frequency_writers[sample_id] = CellularFrequenciesWriter(
file_name,
self.mutation_ids,
sample_id
)
if self.update_precision:
self.precision_writer = PrecisionWriter(paths.get_precision_trace_file(self.config_file))
def run_analysis_pipeline(args):
config_file = _setup_analysis(
density=args.density,
in_files=args.in_files,
init_method=args.init_method,
num_iters=args.num_iters,
samples=args.samples,
prior=args.prior,
tumour_contents=args.tumour_contents,
working_dir=args.working_dir,
config_extras_file=args.config_extras_file,
)
_run_analysis(config_file, args.seed)
tables_dir = os.path.join(args.working_dir, 'tables')
make_directory(tables_dir)
for table_type in ['cluster', 'loci']:
out_file = os.path.join(tables_dir, '{0}.tsv'.format(table_type))
_build_table(config_file=config_file,
out_file=out_file,
burnin=args.burnin,
max_clusters=args.max_clusters,
mesh_size=args.mesh_size,
table_type=table_type,
thin=args.thin)
plots_dir = os.path.join(args.working_dir, 'plots')
plots = [('cluster', 'density'), ('cluster', 'parallel_coordinates'),
('cluster', 'scatter'), ('loci', 'density'),
('loci', 'parallel_coordinates'), ('loci', 'scatter'),
('loci', 'similarity_matrix'),
('loci', 'vaf_parallel_coordinates'), ('loci', 'vaf_scatter')]
for category, plot_type in plots:
plot_file = os.path.join(
plots_dir, category, '{0}.{1}'.format(plot_type,
args.plot_file_format))
make_parent_directory(plot_file)
if category == 'cluster':
_cluster_plot(config_file, plot_file, args.burnin,
args.max_clusters, args.mesh_size,
args.min_cluster_size, plot_type, args.samples,
args.thin)
elif category == 'loci':
_loci_plot(config_file,
plot_file,
plot_type,
burnin=args.burnin,
min_cluster_size=args.min_cluster_size,
samples=args.samples,
thin=args.thin)