def __init__(self, args = {}, p=progress, r=run):
self.args = args
self.splits_of_interest = set([])
self.samples_of_interest = set([])
self.run = r
self.progress = p
A = lambda x, t: t(args.__dict__[x]) if args.__dict__.has_key(x) else None
null = lambda x: x
self.bin_id = A('bin_id', null)
self.collection_id = A('collection_id', null)
self.splits_of_interest_path = A('splits_of_interest', null)
self.min_ratio = A('min_ratio', float)
self.min_occurrence = A('min_occurrence', int)
self.num_positions_from_each_split = A('num_positions_from_each_split', int)
self.min_scatter = A('min_scatter', int)
self.min_coverage_in_each_sample = A('min_coverage_in_each_sample', int)
self.profile_db_path = A('profile_db', null)
self.contigs_db_path = A('contigs_db', null)
self.quince_mode = A('quince_mode', bool)
self.output_file_path = A('output_file', null)
self.samples_of_interest_path = A('samples_of_interest', null)
self.variable_nts_table = {}
self.merged_split_coverage_values = None
self.unique_pos_identifier = 0
self.split_name_position_dict = {}
self.unique_pos_id_to_entry_id = {}
self.contig_sequences = None
self.input_file_path = None
# Initialize the contigs super
dbops.ContigsSuperclass.__init__(self, self.args, r = self.run, p = self.progress)
self.init_contig_sequences()
def __init__(self, args = {}, p=progress, r=run):
self.args = args
self.run = r
self.progress = p
self.samples = None
self.samples_information_dict = None
self.data = None
A = lambda x, t: t(args.__dict__[x]) if args.__dict__.has_key(x) else None
null = lambda x: x
self.input_file_path = A('input_file', null)
self.samples_information_path = A('samples_information', null)
self.max_num_unique_positions = A('max_num_unique_positions', int)
self.output_file_path = A('output_file', null)
filesnpaths.is_output_file_writable(self.output_file_path)
if self.samples_information_path:
filesnpaths.is_file_tab_delimited(self.samples_information_path)
self.samples_information_dict = utils.get_TAB_delimited_file_as_dictionary(self.samples_information_path)
num_attributes = len(self.samples_information_dict.values()[0])
self.run.info('samples_information', '%d attributes read for %d samples' % (num_attributes, len(self.samples_information_dict)))
if self.input_file_path:
filesnpaths.is_file_tab_delimited(self.input_file_path)
self.progress.new('Reading the input file')
self.progress.update('...')
self.data = utils.get_TAB_delimited_file_as_dictionary(self.input_file_path)
self.progress.end()
self.run.info('input_file', '%d entries read' % len(self.data))
def __init__(self, args, run=terminal.Run(), progress=terminal.Progress()):
self.args = args
self.run = run
self.progress = progress
# initialize self.arg parameters
A = lambda x, t: t(args.__dict__[x]
) if x in self.args.__dict__ else None
null = lambda x: x
self.contigs_db_path = A('contigs_db', null)
self.structure_db_path = A('structure_db', null)
self.genes_to_remove = A('genes_to_remove', null)
self.genes_to_remove_path = A('genes_to_remove_file', null)
self.genes_to_add = A('genes_to_add', null)
self.genes_to_add_path = A('genes_to_add_file', null)
self.full_modeller_output = A('dump_dir', null)
self.modeller_executable = A('modeller_executable', null)
self.DSSP_executable = None
utils.is_contigs_db(self.contigs_db_path)
self.contigs_db = dbops.ContigsDatabase(self.contigs_db_path)
self.contigs_db_hash = self.contigs_db.meta['contigs_db_hash']
# init ContigsSuperClass
self.contigs_super = ContigsSuperclass(self.args)
if not any([
self.genes_to_remove, self.genes_to_remove_path,
self.genes_to_add, self.genes_to_add_path
]):
raise ConfigError(
"Please specify some genes to add or remove to your database.")
if self.genes_to_remove and self.genes_to_remove_path:
raise ConfigError(
"Provide either --genes-to-remove or --genes-to-remove-path. You provided both."
)
if self.genes_to_add and self.genes_to_add_path:
raise ConfigError(
"Provide either --genes-to-add or --genes-to-add-path. You provided both."
)
if self.genes_to_remove or self.genes_to_remove_path:
self.run.warning("Removing genes...",
header="Updating %s" % self.structure_db_path,
lc='green')
self.load_structure_db()
remove = self.parse_genes(self.genes_to_remove,
self.genes_to_remove_path)
self.remove_genes(remove)
self.structure_db.disconnect()
if self.genes_to_add or self.genes_to_add_path:
self.run.warning("Adding genes...",
header="Updating %s" % self.structure_db_path,
lc='green')
self.load_structure_db()
self.add_genes()
def __init__(self, args={}, p=progress, r=run):
self.args = args
self.data = {}
self.splits_of_interest = set([])
self.samples_of_interest = set([])
A = lambda x, t: t(args.__dict__[x]) if x in args.__dict__ else None
null = lambda x: x
self.bin_id = A('bin_id', null)
self.collection_name = A('collection_name', null)
self.splits_of_interest_path = A('splits_of_interest', null)
self.min_departure_from_reference = A('min_departure_from_reference',
float)
self.max_departure_from_reference = A('max_departure_from_reference',
float)
self.min_departure_from_consensus = A('min_departure_from_consensus',
float)
self.max_departure_from_consensus = A('max_departure_from_consensus',
float)
self.min_occurrence = A('min_occurrence', int)
self.num_positions_from_each_split = A('num_positions_from_each_split',
int)
self.min_scatter = A('min_scatter', int)
self.min_coverage_in_each_sample = A('min_coverage_in_each_sample',
int)
self.profile_db_path = A('profile_db', null)
self.contigs_db_path = A('contigs_db', null)
self.quince_mode = A('quince_mode', bool)
self.output_file_path = A('output_file', null)
self.samples_of_interest_path = A('samples_of_interest', null)
self.genes_of_interest_path = A('genes_of_interest', null)
self.include_contig_names_in_output = A('include_contig_names', null)
self.include_split_names_in_output = A('include_split_names', null)
self.merged_split_coverage_values = None
self.unique_pos_identifier = 0
self.split_name_position_dict = {}
self.unique_pos_id_to_entry_id = {}
self.contig_sequences = None
self.input_file_path = None
if self.engine not in variability_engines:
raise ConfigError, "The superclass is inherited with an unknown engine. Anvi'o needs an adult :("
# Initialize the contigs super
dbops.ContigsSuperclass.__init__(self,
self.args,
r=self.run,
p=self.progress)
self.init_contig_sequences()
def __init__(self, args, run=terminal.Run(), progress=terminal.Progress()):
self.args = args
self.run = run
self.progress = progress
# initialize self.arg parameters
A = lambda x, t: t(args.__dict__[x]) if x in self.args.__dict__ else None
null = lambda x: x
self.contigs_db_path = A('contigs_db', null)
self.structure_db_path = A('structure_db', null)
self.genes_to_remove = A('genes_to_remove', null)
self.genes_to_remove_path = A('genes_to_remove_file', null)
self.genes_to_add = A('genes_to_add', null)
self.genes_to_add_path = A('genes_to_add_file', null)
self.full_modeller_output = A('dump_dir', null)
self.modeller_executable = A('modeller_executable', null)
self.skip_genes_if_already_present = A('skip_genes_if_already_present', bool)
self.DSSP_executable = None
utils.is_contigs_db(self.contigs_db_path)
self.contigs_db = dbops.ContigsDatabase(self.contigs_db_path)
self.contigs_db_hash = self.contigs_db.meta['contigs_db_hash']
# init ContigsSuperClass
self.contigs_super = ContigsSuperclass(self.args)
if not any([self.genes_to_remove, self.genes_to_remove_path, self.genes_to_add, self.genes_to_add_path]):
raise ConfigError("Please specify some genes to add or remove to your database.")
if self.genes_to_remove and self.genes_to_remove_path:
raise ConfigError("Provide either --genes-to-remove or --genes-to-remove-path. You provided both.")
if self.genes_to_add and self.genes_to_add_path:
raise ConfigError("Provide either --genes-to-add or --genes-to-add-path. You provided both.")
if self.genes_to_remove or self.genes_to_remove_path:
self.run.warning("Removing genes...", header="Updating %s" % self.structure_db_path, lc='green')
self.load_structure_db()
remove = self.parse_genes(self.genes_to_remove, self.genes_to_remove_path)
self.remove_genes(remove)
self.structure_db.disconnect()
if self.genes_to_add or self.genes_to_add_path:
self.run.warning("Adding genes...", header="Updating %s" % self.structure_db_path, lc='green')
self.load_structure_db()
self.add_genes()
def __init__(self, args={}, p=progress, r=run):
self.args = args
self.data = {}
self.splits_of_interest = set([])
self.samples_of_interest = set([])
A = lambda x, t: t(args.__dict__[x]) if x in args.__dict__ else None
null = lambda x: x
self.bin_id = A('bin_id', null)
self.collection_name = A('collection_name', null)
self.splits_of_interest_path = A('splits_of_interest', null)
self.min_departure_from_reference = A('min_departure_from_reference', float)
self.max_departure_from_reference = A('max_departure_from_reference', float)
self.min_departure_from_consensus = A('min_departure_from_consensus', float)
self.max_departure_from_consensus = A('max_departure_from_consensus', float)
self.min_occurrence = A('min_occurrence', int)
self.num_positions_from_each_split = A('num_positions_from_each_split', int)
self.min_scatter = A('min_scatter', int)
self.min_coverage_in_each_sample = A('min_coverage_in_each_sample', int)
self.profile_db_path = A('profile_db', null)
self.contigs_db_path = A('contigs_db', null)
self.quince_mode = A('quince_mode', bool)
self.output_file_path = A('output_file', null)
self.samples_of_interest_path = A('samples_of_interest', null)
self.genes_of_interest_path = A('genes_of_interest', null)
self.include_contig_names_in_output = A('include_contig_names', null)
self.include_split_names_in_output = A('include_split_names', null)
self.merged_split_coverage_values = None
self.unique_pos_identifier = 0
self.split_name_position_dict = {}
self.unique_pos_id_to_entry_id = {}
self.contig_sequences = None
self.input_file_path = None
if self.engine not in variability_engines:
raise ConfigError, "The superclass is inherited with an unknown engine. Anvi'o needs an adult :("
# Initialize the contigs super
dbops.ContigsSuperclass.__init__(self, self.args, r=self.run, p=self.progress)
self.init_contig_sequences()
def __init__(self, args={}, p=progress, r=run):
self.args = args
self.splits_of_interest = set([])
self.samples_of_interest = set([])
self.run = r
self.progress = p
A = lambda x, t: t(args.__dict__[x]) if args.__dict__.has_key(
x) else None
null = lambda x: x
self.bin_id = A('bin_id', null)
self.collection_id = A('collection_id', null)
self.splits_of_interest_path = A('splits_of_interest', null)
self.min_ratio = A('min_ratio', float)
self.min_occurrence = A('min_occurrence', int)
self.num_positions_from_each_split = A('num_positions_from_each_split',
int)
self.min_scatter = A('min_scatter', int)
self.min_coverage_in_each_sample = A('min_coverage_in_each_sample',
int)
self.profile_db_path = A('profile_db', null)
self.contigs_db_path = A('contigs_db', null)
self.quince_mode = A('quince_mode', bool)
self.output_file_path = A('output_file', null)
self.samples_of_interest_path = A('samples_of_interest', null)
self.variable_nts_table = {}
self.merged_split_coverage_values = None
self.unique_pos_identifier = 0
self.split_name_position_dict = {}
self.unique_pos_id_to_entry_id = {}
self.contig_sequences = None
self.input_file_path = None
# Initialize the contigs super
dbops.ContigsSuperclass.__init__(self,
self.args,
r=self.run,
p=self.progress)
self.init_contig_sequences()
def __init__(self, args = {}, p=progress, r=run):
self.args = args
self.splits_of_interest = set([])
self.samples_of_interest = set([])
A = lambda x, t: t(args.__dict__[x]) if args.__dict__.has_key(x) else None
null = lambda x: x
self.bin_id = A('bin_id', null)
self.collection_name = A('collection_name', null)
self.splits_of_interest_path = A('splits_of_interest', null)
self.min_ratio = A('min_ratio', float)
self.min_occurrence = A('min_occurrence', int)
self.num_positions_from_each_split = A('num_positions_from_each_split', int)
self.min_scatter = A('min_scatter', int)
self.min_coverage_in_each_sample = A('min_coverage_in_each_sample', int)
self.profile_db_path = A('profile_db', null)
self.contigs_db_path = A('contigs_db', null)
self.quince_mode = A('quince_mode', bool)
self.output_file_path = A('output_file', null)
self.samples_of_interest_path = A('samples_of_interest', null)
def __init__(self, args={}, p=progress, r=run):
self.args = args
self.run = r
self.progress = p
self.samples = None
self.samples_information_dict = None
self.variable_nts_table = None
A = lambda x, t: t(args.__dict__[x]) if args.__dict__.has_key(
x) else None
null = lambda x: x
self.input_file_path = A('input_file', null)
self.samples_information_path = A('samples_information', null)
self.max_num_unique_positions = A('max_num_unique_positions', int)
self.output_file_path = A('output_file', null)
filesnpaths.is_output_file_writable(self.output_file_path)
if self.samples_information_path:
filesnpaths.is_file_tab_delimited(self.samples_information_path)
self.samples_information_dict = utils.get_TAB_delimited_file_as_dictionary(
self.samples_information_path)
num_attributes = len(self.samples_information_dict.values()[0])
self.run.info(
'samples_information', '%d attributes read for %d samples' %
(num_attributes, len(self.samples_information_dict)))
if self.input_file_path:
filesnpaths.is_file_tab_delimited(self.input_file_path)
self.progress.new('Reading the input file')
self.progress.update('...')
self.variable_nts_table = utils.get_TAB_delimited_file_as_dictionary(
self.input_file_path)
self.progress.end()
self.run.info('input_file',
'%d entries read' % len(self.variable_nts_table))
def __init__(self, args, run=terminal.Run(), progress=terminal.Progress()):
self.args = args
self.run = run
self.progress = progress
# initialize self.arg parameters
A = lambda x, t: t(args.__dict__[x]) if x in self.args.__dict__ else None
null = lambda x: x
self.contigs_db_path = A('contigs_db', null)
self.genes_of_interest_path = A('genes_of_interest', null)
self.splits_of_interest_path = A('splits_of_interest', null)
self.bin_id = A('bin_id', null)
self.collection_name = A('collection_name', null)
self.gene_caller_ids = A('gene_caller_ids', null)
self.output_db_path = A('output_db_path', null)
self.full_modeller_output = A('dump_dir', null)
self.skip_DSSP = A('skip_DSSP', bool)
self.modeller_executable = A('modeller_executable', null)
self.DSSP_executable = None
utils.is_contigs_db(self.contigs_db_path)
self.contigs_db = dbops.ContigsDatabase(self.contigs_db_path)
self.contigs_db_hash = self.contigs_db.meta['contigs_db_hash']
# MODELLER params
self.modeller_database = A('modeller_database', null)
self.scoring_method = A('scoring_method', null)
self.max_number_templates = A('max_number_templates', null)
self.percent_identical_cutoff = A('percent_identical_cutoff', null)
self.num_models = A('num_models', null)
self.deviation = A('deviation', null)
self.very_fast = A('very_fast', bool)
# check database output
if not self.output_db_path:
self.output_db_path = "STRUCTURE.db"
if not self.output_db_path.endswith('.db'):
raise ConfigError("The structure database output file (`-o / --output`) must end with '.db'")
filesnpaths.is_output_file_writable(self.output_db_path)
# check modeller output
if self.full_modeller_output:
self.full_modeller_output = filesnpaths.check_output_directory(self.full_modeller_output, ok_if_exists=False)
# identify which genes user wants to model structures for
self.genes_of_interest = self.get_genes_of_interest(self.genes_of_interest_path, self.gene_caller_ids)
self.sanity_check()
# residue annotation
self.residue_annotation_sources_info = self.get_residue_annotation_sources_info()
self.residue_info_table_structure, self.residue_info_table_types = self.get_residue_info_table_structure()
self.residue_annotation_df = pd.DataFrame({})
# initialize StructureDatabase
self.structure_db = StructureDatabase(self.output_db_path,
self.contigs_db_hash,
residue_info_structure_extras = self.residue_info_table_structure,
residue_info_types_extras = self.residue_info_table_types,
create_new=True)
# init ContigsSuperClass
self.contigs_super = ContigsSuperclass(self.args)
def __init__(self, args, run=terminal.Run(), progress=terminal.Progress()):
self.args = args
self.run = run
self.progress = progress
# initialize self.arg parameters
A = lambda x, t: t(args.__dict__[x]
) if x in self.args.__dict__ else None
null = lambda x: x
self.contigs_db_path = A('contigs_db', null)
self.genes_of_interest_path = A('genes_of_interest', null)
self.splits_of_interest_path = A('splits_of_interest', null)
self.bin_id = A('bin_id', null)
self.collection_name = A('collection_name', null)
self.gene_caller_ids = A('gene_caller_ids', null)
self.output_db_path = A('output_db_path', null)
self.full_modeller_output = A('dump_dir', null)
self.skip_DSSP = A('skip_DSSP', bool)
self.modeller_executable = A('modeller_executable', null)
self.DSSP_executable = None
utils.is_contigs_db(self.contigs_db_path)
self.contigs_db = dbops.ContigsDatabase(self.contigs_db_path)
self.contigs_db_hash = self.contigs_db.meta['contigs_db_hash']
# MODELLER params
self.modeller_database = A('modeller_database', null)
self.scoring_method = A('scoring_method', null)
self.max_number_templates = A('max_number_templates', null)
self.percent_identical_cutoff = A('percent_identical_cutoff', null)
self.num_models = A('num_models', null)
self.deviation = A('deviation', null)
self.very_fast = A('very_fast', bool)
# check database output
if not self.output_db_path:
self.output_db_path = "STRUCTURE.db"
if not self.output_db_path.endswith('.db'):
raise ConfigError(
"The structure database output file (`-o / --output`) must end with '.db'"
)
filesnpaths.is_output_file_writable(self.output_db_path)
# check modeller output
if self.full_modeller_output:
self.full_modeller_output = filesnpaths.check_output_directory(
self.full_modeller_output, ok_if_exists=False)
# identify which genes user wants to model structures for
self.genes_of_interest = self.get_genes_of_interest(
self.genes_of_interest_path, self.gene_caller_ids)
self.sanity_check()
# residue annotation
self.annotation_sources_info = self.get_annotation_sources_info()
self.residue_info_table_structure, self.residue_info_table_types = self.get_residue_info_table_structure(
)
self.res_annotation_df = pd.DataFrame({})
# initialize StructureDatabase
self.structure_db = StructureDatabase(
self.output_db_path,
self.contigs_db_hash,
residue_info_structure_extras=self.residue_info_table_structure,
residue_info_types_extras=self.residue_info_table_types,
create_new=True)
# init ContigsSuperClass
self.contigs_super = ContigsSuperclass(self.args)
