def get_log(self):
ribo_utils.make_dir(
os.path.join(self.experiment_settings.get_rdir(), 'logs'))
log = os.path.join(
self.experiment_settings.get_rdir(), 'logs',
'%(sample_name)s.log' % {'sample_name': self.sample_name})
return log
def make_genome_mapping_index(self):
make_index = False
if ribo_utils.file_exists(
self.settings.get_property('star_genome_dir')):
self.settings.write_to_log(
'STAR index exists at %s' %
self.settings.get_property('star_genome_dir'))
if self.settings.get_property('rebuild_star_index'):
self.settings.write_to_log('STAR index rebuild forced')
make_index = True
else:
self.settings.write_to_log('using existing STAR index')
else:
make_index = True
ribo_utils.make_dir(self.settings.get_property('star_genome_dir'))
if make_index:
self.settings.write_to_log('building STAR index')
if self.settings.get_property('transcriptome_mapping_only'):
command_to_run = 'STAR --runThreadN %d --runMode genomeGenerate --genomeDir %s --genomeFastaFiles %s --genomeSAsparseD %d 1>>%s 2>>%s' % (
self.threads,
self.settings.get_property('star_genome_dir'),
self.settings.get_transcriptome_FASTA(),
self.settings.get_property('star_index_sparsity'),
self.settings.get_log(), self.settings.get_log())
else:
command_to_run = 'STAR --runThreadN %d --runMode genomeGenerate --genomeDir %s --genomeFastaFiles %s*.fa --genomeSAsparseD %d 1>>%s 2>>%s' % (
self.threads,
self.settings.get_property('star_genome_dir'),
self.settings.get_genome_sequence_dir(),
self.settings.get_property('star_index_sparsity'),
self.settings.get_log(), self.settings.get_log())
self.settings.write_to_log(command_to_run)
subprocess.Popen(command_to_run, shell=True).wait()
self.settings.write_to_log('STAR index ready')
def make_tables(self):
ribo_utils.make_dir(self.rdir_path('tables'))
ribo_tables.make_readthrough_table(self)
ribo_tables.make_detailed_readthrough_table(self)
ribo_tables.transcriptome_features_table(self)
ribo_tables.make_cds_rpkm_table(self)
ribo_tables.make_cds_counts_table(self)
def map_reads_to_ncrna(self):
"""
map all reads using bowtie
:return:
"""
if not self.settings.get_property('force_remapping'):
for lib_settings in self.settings.iter_lib_settings():
if not lib_settings.ncrna_mapped_reads_exist():
break
else:
self.settings.write_to_log(
'using existing noncoding RNA mapped reads')
return
else:
self.settings.write_to_log('remapping forced')
self.settings.write_to_log('mapping reads')
ribo_utils.make_dir(self.rdir_path('ncrna_mapped_reads'))
ribo_utils.parmap(lambda lib_setting: self.map_one_library_to_ncrna(
lib_setting, self.genome_threads_per_instance), [
lib_setting
for lib_setting in self.settings.iter_lib_settings()
if not lib_setting.ncrna_mapping_finished()
],
nprocs=self.genome_num_instances)
self.settings.write_to_log('finished mapping reads to noncoding RNA')
def initialize_libs(self):
self.settings.write_to_log('initializing libraries, counting reads')
ribo_utils.make_dir(self.rdir_path('transcript_counts'))
self.libs = []
ribo_utils.parmap(lambda lib_settings: ribo_lib.assign_tx_reads(
self, self.settings, lib_settings),
self.settings.iter_lib_settings(),
nprocs=self.threads)
map(lambda lib_settings: self.initialize_lib(lib_settings),
self.settings.iter_lib_settings())
self.settings.write_to_log(
'initializing libraries, counting reads, done')
def deduplicate_reads(self):
for lib_settings in self.settings.iter_lib_settings():
if not lib_settings.deduplicated_reads_exist():
break
else: #else clause executes if break did not occur
self.settings.write_to_log('using existing deduplicated reads')
return
self.settings.write_to_log('deduplicating reads with tally')
ribo_utils.make_dir(self.rdir_path('deduplicated'))
ribo_utils.parmap(
lambda lib_setting: self.deduplicate_reads_one_lib(lib_setting),
self.settings.iter_lib_settings(),
nprocs=self.num_instances)
self.settings.write_to_log('done deduplicating reads with tally')
def __init__(self, settings, threads):
self.threads = threads
self.settings = settings
self.all_settings = [
lib_setting for lib_setting in self.settings.iter_lib_settings()
]
self.num_datasets = len(self.all_settings)
self.num_instances = min(self.num_datasets, self.threads)
self.threads_per_instance = max(self.threads / self.num_instances - 1,
1)
self.genome_num_instances = min(min(self.num_datasets, self.threads),
5)
self.genome_threads_per_instance = max(
self.threads / self.genome_num_instances, 1)
self.settings.write_to_log(
'Initializing experiment %s' %
self.settings.get_property('experiment_name'))
self.num_libs = len([x for x in settings.iter_lib_settings()])
self.make_ncRNA_mapping_index()
self.settings.write_to_log('loading GTF annotations')
self.GTF_annotations = ribo_utils.gtf_data(
self.settings.get_annotation_GTF_file(),
add_3_for_stop=self.settings.get_property('add_3_for_stop'))
self.settings.write_to_log('loading genome sequence')
self.genome = ribo_utils.genome_sequence(
self.settings.get_genome_sequence_files())
if self.settings.get_property('transcriptome_mapping_only'):
#only mapping to the transcriptome, not the genome, so need to generate the genome to map to
ribo_utils.make_dir(self.settings.get_transcriptome_dir())
self.GTF_annotations.write_transcript_sequences_to_FASTA(
self.settings.get_transcriptome_FASTA(), self.genome)
self.settings.write_to_log('loading transcriptome sequence')
self.transcriptome_sequence = ribo_utils.genome_sequence(
self.settings.get_transcriptome_FASTA())
self.make_genome_mapping_index()
self.deduplicate_reads()
self.trim_reads()
self.remove_adaptor()
self.map_reads_to_ncrna()
self.map_reads_to_genome()
self.initialize_libs()
self.settings.write_to_log(
'Finished initializing experiment %s\n' %
self.settings.get_property('experiment_name'))
def remove_adaptor(self):
if not self.settings.get_property('force_retrim'):
for lib_settings in self.settings.iter_lib_settings():
if not lib_settings.adaptorless_reads_exist():
break
else:
self.settings.write_to_log('using existing adaptorless reads')
return
else:
self.settings.write_to_log('adaptor removal forced')
self.settings.write_to_log('removing adaptors')
ribo_utils.make_dir(self.rdir_path('adaptor_removed'))
ribo_utils.parmap(lambda lib_setting: self.remove_adaptor_one_lib(
lib_setting, self.threads_per_instance),
self.settings.iter_lib_settings(),
nprocs=self.num_instances)
self.settings.write_to_log('done removing adaptors')
def trim_reads(self):
if not self.settings.get_property('force_retrim'):
for lib_settings in self.settings.iter_lib_settings():
if not lib_settings.trimmed_reads_exist():
break
else: #else clause executes if break did not occur
self.settings.write_to_log('using existing trimmed reads')
return
else:
self.settings.write_to_log('read trimming forced')
self.settings.write_to_log('trimming reads with seqtk')
ribo_utils.make_dir(self.rdir_path('trimmed'))
ribo_utils.parmap(lambda lib_setting: self.trim_reads_one_lib(
lib_setting, self.threads_per_instance),
self.settings.iter_lib_settings(),
nprocs=self.num_instances)
self.settings.write_to_log('done trimming reads with seqtk')
def __init__(self, experiment, experiment_settings, threads):
"""
Constructor for Library class
"""
self.threads = threads
self.experiment = experiment
self.experiment_settings = experiment_settings
self.experiment_settings.write_to_log('initializing QC engine')
self.get_property = self.experiment_settings.get_property
self.get_rdir = experiment_settings.get_rdir
ribo_utils.make_dir(self.experiment.rdir_path('QC'))
self.genome = self.experiment.genome
self.full_QC_GTF_annotations = ribo_utils.gtf_data(
self.experiment_settings.get_QC_annotation_GTF_file(),
add_3_for_stop=self.experiment_settings.get_property(
'add_3_for_stop'))
self.lib_QCs = [
self.initialize_qc_lib(lib_settings)
for lib_settings in self.experiment_settings.iter_lib_settings()
]
def make_plots(self):
ribo_utils.make_dir(self.rdir_path('plots'))
ribo_plotting.plot_start_codon_average(
self,
up=100,
down=100,
min_cds_reads=self.settings.get_property('comparison_read_cutoff'),
read_end='3p',
read_lengths='all')
ribo_plotting.plot_stop_codon_average(
self,
up=100,
down=100,
min_cds_reads=self.settings.get_property('comparison_read_cutoff'),
read_end='3p',
read_lengths='all')
ribo_plotting.plot_fragment_length_distributions(self)
ribo_plotting.plot_frame_distributions(self)
def process_settings(self, settings_file):
"""
- reads the settings file and converts str to float, list, etc.
- stores result in self.settings as a dict()
- CRITICAL NOTE: All keys must be lower case
"""
# TODO: Add new parameters and comments to settings files
int_keys = [
'comparison_read_cutoff', 'min_post_trimming_length',
'max_post_trimming_length', 'sequence_quality_cutoff', 'trim_5p',
'star_index_sparsity', 'outfiltermultimapnmax',
'outfiltermismatchnmax', 'alignsjdboverhangmin',
'alignsjoverhangmin', 'alignintronmax', 'five_prime_p_offset'
]
float_keys = ['atail_purity_cutoff']
str_keys = [
'adaptor_3p_sequence', 'star_genome_dir', 'star_ncrna_dir',
'genome_sequence_dir', 'ncrna_sequence_dir', 'annotation_gtf_file',
'qc_annotation_gtf_file', 'alignendstype'
]
#if transcriptome_only is true, will genreate a transcriptome-only genome to map to
boolean_keys = [
'transcriptome_mapping_only', 'deduplicate_reads',
'force_remapping', 'force_recount', 'rebuild_star_index',
'force_retrim', 'make_interactive_plots', 'reads_reversed',
'add_3_for_stop', 'forbid_non_polya_soft_clip',
'unique_mapping_only'
]
list_str_keys = ['fastq_gz_files', 'sample_names']
#list_float_keys = ['concentrations', 'input_rna']
extant_files = ['genome_sequence_dir', 'annotation_gtf_file']
config = ConfigParser.ConfigParser()
config.read(settings_file)
settings = {}
for section in config.sections():
for option in config.options(section):
settings[option] = config.get(section, option)
settings[section] = True
for k in int_keys:
settings[k] = int(settings[k])
for k in str_keys:
settings[k] = settings[k]
for k in float_keys:
settings[k] = float(settings[k])
for k in boolean_keys:
if not settings[k].lower() in ['true', 'false']:
raise ValueError('Boolean value %s must be "true" or "false"' %
k)
settings[k] = settings[k].lower() == 'true'
#for k in list_float_keys:
# settings[k] = map(float, simplejson.loads(settings[k]))
#for k in list_int_keys:
# settings[k] = map(int, simplejson.loads(settings[k]))
for k in list_str_keys:
settings[k] = simplejson.loads(settings[k])
self.fqdir = settings['fastq_dir']
self.sample_names = settings['sample_names']
self.fastq_gz_files = settings['fastq_gz_files']
self.fastq_gz_file_handles = [
os.path.join(self.fqdir, fastq_gz_file)
for fastq_gz_file in self.fastq_gz_files
]
for file_handle in self.fastq_gz_file_handles:
try:
assert ribo_utils.file_exists(file_handle)
except:
print 'ERROR: nonexistent file ', file_handle
sys.exit()
for k in extant_files:
try:
assert ribo_utils.file_exists(settings[k])
except AssertionError:
print 'file %s does not exist' % settings[k]
sys.exit()
self.settings = settings
self.rdir = settings['results_dir']
ribo_utils.make_dir(self.rdir)
shutil.copy(settings_file, self.rdir)
def get_rdir(self):
ribo_utils.make_dir(self.rdir)
return self.rdir
