def __init__(self, args, hmm_sources):
self.args = args
self.hmm_sources = hmm_sources
self.splits_dict = {}
# initialize the super
SequencesForHMMHits.__init__(self, None, sources=hmm_sources)
# process genome descriptions
GenomeDescriptions.__init__(self, args)
self.load_genomes_descriptions(skip_functions=True, init=False)
hmm_sources_in_all_genomes = self.get_HMM_sources_common_to_all_genomes()
# very hacky code follows. here we generate a self SequencesForHMMHits object,
# and we will fill everything in it with slightly modified information so multiple
# contigs databases could be processed by this talented class seamlessly.
hmm_hits_splits_counter = 0
for genome_name in self.genomes:
contigs_db_path = self.genomes[genome_name]['contigs_db_path']
contigs_db_hash = self.genomes[genome_name]['contigs_db_hash']
current = SequencesForHMMHits(contigs_db_path, sources = hmm_sources)
for hmm_hit_id in current.hmm_hits:
hit = current.hmm_hits[hmm_hit_id]
hit['gene_callers_id'] = '%s_%d' % (contigs_db_hash, hit['gene_callers_id'])
self.hmm_hits['%s_%d' % (contigs_db_hash, hmm_hit_id)] = hit
if not self.hmm_hits_info:
for hmm_source in hmm_sources_in_all_genomes:
self.hmm_hits_info[hmm_source] = current.hmm_hits_info[hmm_source]
for hit in current.hmm_hits_splits.values():
hit['split'] = '%s_%s' % (contigs_db_hash, hit['split'])
hit['hmm_hit_entry_id'] = '%s_%d'% (contigs_db_hash, hit['hmm_hit_entry_id'])
self.hmm_hits_splits[hmm_hits_splits_counter] = hit
hmm_hits_splits_counter += 1
for seq in current.contig_sequences:
self.contig_sequences['%s_%s' % (contigs_db_hash, seq)] = current.contig_sequences[seq]
for seq in current.aa_sequences:
self.aa_sequences['%s_%s' % (contigs_db_hash, seq)] = current.aa_sequences[seq]
for gene_callers_id in current.genes_in_contigs:
entry = current.genes_in_contigs[gene_callers_id]
entry['contig'] = '%s_%s' % (contigs_db_hash, entry['contig'])
self.genes_in_contigs['%s_%d' % (contigs_db_hash, gene_callers_id)] = entry
self.splits_dict[genome_name] = ['%s_%s' % (contigs_db_hash, s) for s in current.splits_in_contigs]
def __init__(self, args=None, run=run, progress=progress):
self.args = args
self.run = run
self.progress = progress
GenomeDescriptions.__init__(self, args, self.run, self.progress)
self.storage_path = None
self.genomes_storage = None
self.genome_names_to_focus = None
self.hash_to_genome_name = {}
self.functions_are_available = False
self.function_annotation_sources = set([])
def __init__(self,
args,
hmm_sources,
run=terminal.Run(),
progress=terminal.Progress()):
self.args = args
self.run = run
self.progress = progress
self.hmm_sources = hmm_sources
self.splits_dict = {}
# process genome descriptions
GenomeDescriptions.__init__(self,
args,
run=self.run,
progress=self.progress)
self.load_genomes_descriptions(skip_functions=True, init=False)
hmm_sources_in_all_genomes = self.get_HMM_sources_common_to_all_genomes(
sources_that_must_be_common=hmm_sources)
if not len(hmm_sources_in_all_genomes):
raise ConfigError(
"There are no HMM sources among your external genomes that occur in every genome :/"
)
# initialize the super
SequencesForHMMHits.__init__(self,
None,
sources=hmm_sources,
run=self.run,
progress=self.progress)
num_internal_genomes = len(
set([
g['genome_hash'] for g in self.genomes.values()
if 'profile_db_path' in g
]))
collection_names = set([
g['collection_id'] for g in self.genomes.values()
if 'collection_id' in g
])
if num_internal_genomes:
self.run.warning(
"SequencesForHMMHitsWrapperForMultipleContigs class is speaking (yes, the class is "
"quite aware of its very long name thankyouverymuch). Of the total %d genome descriptions "
"it was given, %d seem to represent internal genomes with bins in collection(s) '%s'. Anvi'o "
"will make sure HMM hits to be used for downstream analyses are only those that match to contigs "
"that were included in those selections." %
(len(self.genomes), num_internal_genomes,
', '.join(collection_names)),
lc="green")
# very hacky code follows. here we generate a self SequencesForHMMHits object,
# and we will fill everything in it with slightly modified information so multiple
# contigs databases could be processed by this talented class seamlessly.
hmm_hits_splits_counter = 0
for genome_name in self.genomes:
g = self.genomes[genome_name]
contigs_db_path = g['contigs_db_path']
contigs_db_hash = g['contigs_db_hash']
# this is an important variable and allows us to track origins of HMM hits for bins
# and individual contigs databases seamlessly. if you want to understand truly what
# the hell does this mean, look at `get_genome_hash_for_external_genome` and
# `get_genome_hash_for_internal_genome` functions in `genomedescriptions.py`.
genome_hash = None
# here we check if the genome descriptions contain reference to a collection name,
# because if it is the case, we need to focus only on hmm hits that are relevant
# to splits in this collection:
if 'collection_id' in g:
if ('bin_id' not in g) or ('profile_db_path' not in g):
raise ConfigError(
"There is something VERY weird going on. Your genome descriptions object contains "
"a collection name, yet it doesn't know anything about a bin name or profile database "
"path. While this is very interesting because it should never happen, anvi'o will say "
"goodbye and abruptly quit in confusion :(")
# setup an args object, and recover the split names of interest
args = argparse.Namespace(profile_db=g['profile_db_path'],
contigs_db=g['contigs_db_path'],
bin_id=g['bin_id'],
collection_name=g['collection_id'])
split_names_of_interest = ccollections.GetSplitNamesInBins(
args).get_split_names_only()
genome_hash = hashlib.sha224('_'.join(
[''.join(split_names_of_interest),
contigs_db_hash]).encode('utf-8')).hexdigest()[0:12]
# current hmm hits now will match to the collection
current = SequencesForHMMHits(
contigs_db_path,
sources=hmm_sources,
split_names_of_interest=split_names_of_interest)
else:
current = SequencesForHMMHits(contigs_db_path,
sources=hmm_sources)
genome_hash = contigs_db_hash
for hmm_hit_id in current.hmm_hits:
hit = current.hmm_hits[hmm_hit_id]
hit['gene_callers_id'] = '%s_%d' % (contigs_db_hash,
hit['gene_callers_id'])
hit['genome_hash'] = genome_hash
self.hmm_hits['%s_%d' % (contigs_db_hash, hmm_hit_id)] = hit
if not self.hmm_hits_info:
for hmm_source in hmm_sources_in_all_genomes:
self.hmm_hits_info[hmm_source] = current.hmm_hits_info[
hmm_source]
for hit in current.hmm_hits_splits.values():
hit['split'] = '%s_%s' % (contigs_db_hash, hit['split'])
hit['hmm_hit_entry_id'] = '%s_%d' % (contigs_db_hash,
hit['hmm_hit_entry_id'])
self.hmm_hits_splits[hmm_hits_splits_counter] = hit
hmm_hits_splits_counter += 1
for seq in current.contig_sequences:
self.contig_sequences['%s_%s' %
(contigs_db_hash,
seq)] = current.contig_sequences[seq]
for seq in current.aa_sequences:
self.aa_sequences['%s_%s' % (contigs_db_hash,
seq)] = current.aa_sequences[seq]
for gene_callers_id in current.genes_in_contigs:
entry = current.genes_in_contigs[gene_callers_id]
entry['contig'] = '%s_%s' % (contigs_db_hash, entry['contig'])
self.genes_in_contigs['%s_%d' % (contigs_db_hash,
gene_callers_id)] = entry
self.splits_dict[genome_name] = [
'%s_%s' % (contigs_db_hash, s)
for s in current.splits_in_contigs
]
def __init__(self, args, hmm_sources, run=terminal.Run(), progress=terminal.Progress()):
self.args = args
self.run = run
self.progress = progress
self.hmm_sources = hmm_sources
self.splits_dict = {}
# initialize the super
SequencesForHMMHits.__init__(self, None, sources=hmm_sources, run=self.run, progress=self.progress)
# process genome descriptions
GenomeDescriptions.__init__(self, args, run=self.run, progress=self.progress)
self.load_genomes_descriptions(skip_functions=True, init=False)
hmm_sources_in_all_genomes = self.get_HMM_sources_common_to_all_genomes()
if not len(hmm_sources_in_all_genomes):
raise ConfigError("There are no HMM sources among your external genomes that occur in every genome :/")
num_internal_genomes = len(set([g['genome_hash'] for g in self.genomes.values() if 'profile_db_path' in g]))
collection_names = set([g['collection_id'] for g in self.genomes.values() if 'collection_id' in g])
if num_internal_genomes:
self.run.warning("SequencesForHMMHitsWrapperForMultipleContigs class is speaking (yes, the class is\
quite aware of its very long name thankyouverymuch). Of the total %d genome descriptions\
it was given, %d seem to represent internal genomes with bins in collection(s) '%s'. Anvi'o\
will make sure HMM hits to be used for downstream analyses are only those that match to contigs\
that were included in those selections." % (len(self.genomes), num_internal_genomes, ', '.join(collection_names)), lc="green")
# very hacky code follows. here we generate a self SequencesForHMMHits object,
# and we will fill everything in it with slightly modified information so multiple
# contigs databases could be processed by this talented class seamlessly.
hmm_hits_splits_counter = 0
for genome_name in self.genomes:
g = self.genomes[genome_name]
contigs_db_path = g['contigs_db_path']
contigs_db_hash = g['contigs_db_hash']
# this is an important variable and allows us to track origins of HMM hits for bins
# and individual contigs databases seamlessly. if you want to understand truly what
# the hell does this mean, look at `get_genome_hash_for_external_genome` and
# `get_genome_hash_for_internal_genome` functions in `genomedescriptions.py`.
genome_hash = None
# here we check if the genome descriptions contain reference to a collection name,
# because if it is the case, we need to focus only on hmm hits that are relevant
# to splits in this collection:
if 'collection_id' in g:
if ('bin_id' not in g) or ('profile_db_path' not in g):
raise ConfigError("There is something VERY weird going on. Your genome descriptions object contains\
a collection name, yet it doesn't know anything about a bin name or profile database\
path. While this is very interesting because it should never happen, anvi'o will say\
goodbye and abruptly quit in confusion :(")
# setup an args object, and recover the split names of interest
args = argparse.Namespace(profile_db=g['profile_db_path'],
contigs_db=g['contigs_db_path'],
bin_id=g['bin_id'],
collection_name=g['collection_id'])
split_names_of_interest=ccollections.GetSplitNamesInBins(args).get_split_names_only()
genome_hash = hashlib.sha224('_'.join([''.join(split_names_of_interest), contigs_db_hash]).encode('utf-8')).hexdigest()[0:12]
# current hmm hits now will match to the collection
current = SequencesForHMMHits(contigs_db_path, sources = hmm_sources, split_names_of_interest=split_names_of_interest)
else:
current = SequencesForHMMHits(contigs_db_path, sources = hmm_sources)
genome_hash = contigs_db_hash
for hmm_hit_id in current.hmm_hits:
hit = current.hmm_hits[hmm_hit_id]
hit['gene_callers_id'] = '%s_%d' % (contigs_db_hash, hit['gene_callers_id'])
hit['genome_hash'] = genome_hash
self.hmm_hits['%s_%d' % (contigs_db_hash, hmm_hit_id)] = hit
if not self.hmm_hits_info:
for hmm_source in hmm_sources_in_all_genomes:
self.hmm_hits_info[hmm_source] = current.hmm_hits_info[hmm_source]
for hit in current.hmm_hits_splits.values():
hit['split'] = '%s_%s' % (contigs_db_hash, hit['split'])
hit['hmm_hit_entry_id'] = '%s_%d'% (contigs_db_hash, hit['hmm_hit_entry_id'])
self.hmm_hits_splits[hmm_hits_splits_counter] = hit
hmm_hits_splits_counter += 1
for seq in current.contig_sequences:
self.contig_sequences['%s_%s' % (contigs_db_hash, seq)] = current.contig_sequences[seq]
for seq in current.aa_sequences:
self.aa_sequences['%s_%s' % (contigs_db_hash, seq)] = current.aa_sequences[seq]
for gene_callers_id in current.genes_in_contigs:
entry = current.genes_in_contigs[gene_callers_id]
entry['contig'] = '%s_%s' % (contigs_db_hash, entry['contig'])
self.genes_in_contigs['%s_%d' % (contigs_db_hash, gene_callers_id)] = entry
self.splits_dict[genome_name] = ['%s_%s' % (contigs_db_hash, s) for s in current.splits_in_contigs]