def run_blast(self, unique_AA_sequences_fasta_path, unique_AA_sequences_names_dict):
self.run.warning("You elected to use NCBI's blastp for amino acid sequence search. Running blastp will \
be significantly slower than DIAMOND (although, anvi'o developers are convinced that \
you *are* doing the right thing, so, kudos to you).")
blast = BLAST(unique_AA_sequences_fasta_path, run=self.run, progress=self.progress,
num_threads=self.num_threads, overwrite_output_destinations=self.overwrite_output_destinations)
blast.names_dict = unique_AA_sequences_names_dict
blast.log_file_path = self.log_file_path
blast.search_output_path = self.get_output_file_path('blast-search-results.txt')
return blast.get_blast_results()
def run_blast(self, unique_AA_sequences_fasta_path,
unique_AA_sequences_names_dict):
self.run.warning(
"You elected to use NCBI's `blastp` for amino acid sequence search. Running blastp will "
"be significantly slower than DIAMOND, but in some cases, slightly more sensitive. "
"We are unsure about whether the slight increase in sensitivity may justify significant "
"increase in run time, but you are the boss.",
lc="cyan")
blast = BLAST(
unique_AA_sequences_fasta_path,
run=self.run,
progress=self.progress,
num_threads=self.num_threads,
overwrite_output_destinations=self.overwrite_output_destinations)
blast.names_dict = unique_AA_sequences_names_dict
blast.log_file_path = self.log_file_path
blast.search_output_path = self.get_output_file_path(
'blast-search-results.txt')
return blast.get_blast_results()
def find(self,
sequence,
sequence_name="(a sequence does not have a name)",
display_palindromes=False):
"""Find palindromes in a single sequence, and populate `self.palindromes`
The member function `process` may be a better one to call with an `args` object. See `anvi-search-palindromes`
for example usage.
"""
if sequence_name in self.palindromes:
raise ConfigError(
f"The sequence '{sequence_name}' is already in `self.palindromes`."
)
else:
self.palindromes[sequence_name] = []
sequence = sequence.upper()
sequence_length = len(sequence)
if sequence_length < self.min_palindrome_length * 2 + self.min_distance:
self.progress.reset()
self.run.warning(
f"The sequence '{sequence_name}', which is only {sequence_length} nts long, is too short "
f"to find palindromes that are at least {self.min_palindrome_length} nts, with "
f"{self.min_distance} nucleoties in between :/ Anvi'o will skip it."
)
# setup BLAST job
BLAST_search_tmp_dir = filesnpaths.get_temp_directory_path()
fasta_file_path = os.path.join(BLAST_search_tmp_dir, 'sequence.fa')
log_file_path = os.path.join(BLAST_search_tmp_dir, 'blast-log.txt')
results_file_path = os.path.join(BLAST_search_tmp_dir, 'hits.xml')
with open(fasta_file_path, 'w') as fasta_file:
fasta_file.write(f'>sequence\n{sequence}\n')
# run blast
blast = BLAST(fasta_file_path,
search_program='blastn',
run=run_quiet,
progress=progress_quiet)
blast.evalue = 10
blast.num_threads = self.num_threads
blast.min_pct_id = 100 - self.max_num_mismatches
blast.search_output_path = results_file_path
blast.log_file_path = log_file_path
blast.makedb(dbtype='nucl')
if self.min_palindrome_length < 20 and len(
sequence
) > 10000 and not self.user_is_warned_for_potential_performance_issues:
self.progress.reset()
self.run.warning(
f"Please note, you are searching for palindromes that are as short as {self.min_palindrome_length} "
f"in a sequence that is {pp(len(sequence))} nts long. If your palindrome search takes a VERY long time "
f"you may want to go for longer palindromes by setting a different `--min-palindrome-length` parameter "
f"and by increasing the BLAST word size using `--blast-word-size` parameter (please read the help menu first). "
f"This part of the code does not know if you have many more seqeunces to search, but anvi'o will not "
f"continue displaying this warning for additional seqeunces to minimize redundant informatio in your "
f"log files (because despite the popular belief anvi'o can actually sometimes be like nice and all).",
header="ONE-TIME PERFORMANCE WARNING")
self.user_is_warned_for_potential_performance_issues = True
blast.blast(outputfmt='5',
word_size=self.blast_word_size,
strand='minus')
# parse the BLAST XML output
root = ET.parse(blast.search_output_path).getroot()
for query_sequence_xml in root.findall(
'BlastOutput_iterations/Iteration'):
for hit_xml in query_sequence_xml.findall('Iteration_hits/Hit'):
for hsp_xml in hit_xml.findall('Hit_hsps/Hsp'):
p = Palindrome(run=self.run)
p.sequence_name = sequence_name
p.first_start = int(
hsp_xml.find('Hsp_query-from').text) - 1
p.first_end = int(hsp_xml.find('Hsp_query-to').text)
p.first_sequence = hsp_xml.find('Hsp_qseq').text
p.second_start = int(hsp_xml.find('Hsp_hit-to').text) - 1
p.second_end = int(hsp_xml.find('Hsp_hit-from').text)
p.second_sequence = hsp_xml.find('Hsp_hseq').text
p.distance = p.second_start - p.first_start
# for each hit, there will be a copy of its reverse complement.
# the first half of the if statement below is to control for that
# and make sure we keep only one of them. the other half is to
# remove those that do not meet the minimum distance criterion.
if p.distance < 0 or p.distance < self.min_distance:
continue
# before we continue, we will test for a special case: internal palindromes
# within larger palindromes of 0 distance. IT DOES HAPPEN I PROM.
if p.distance == 0:
internal_palindrome = False
for _p in self.palindromes[sequence_name]:
if p.first_start > _p.first_start and p.first_start < _p.first_end:
internal_palindrome = True
break
if internal_palindrome:
continue
p.length = int(hsp_xml.find('Hsp_align-len').text)
if p.length < self.min_palindrome_length:
# buckle your seat belt Dorothy, 'cause Kansas is going bye-bye:
continue
p.num_gaps = int(hsp_xml.find('Hsp_gaps').text)
p.num_mismatches = int(
hsp_xml.find('Hsp_align-len').text) - int(
hsp_xml.find('Hsp_identity').text)
p.midline = ''.join([
'|'
if p.first_sequence[i] == p.second_sequence[i] else 'x'
for i in range(0, len(p.first_sequence))
])
if p.num_mismatches > self.max_num_mismatches or p.num_gaps > 0:
# this is the crazy part: read the function docstring for `get_split_palindromes`.
# briefly, we conclude that there are too many mismatches in this match, we will
# try and see if there is anything we can salvage from it.
p_list = self.get_split_palindromes(
p, display_palindromes=display_palindromes)
else:
# there aren't too many mismatches, and the length checks out. we will continue
# processing this hit as a sole palindrome
p_list = [p]
for sp in p_list:
if anvio.DEBUG or display_palindromes or self.verbose:
self.progress.reset()
sp.display()
self.palindromes[sequence_name].append(sp)
# clean after yourself
if anvio.DEBUG:
self.run.info("BLAST temporary dir kept",
BLAST_search_tmp_dir,
nl_before=1,
mc='red')
else:
filesnpaths.shutil.rmtree(BLAST_search_tmp_dir)
def create_search_databases(self):
"""Creates all the search databases"""
self.progress.new("Creating search databases")
self.progress.update(
"Removing any database that still exists in the output directory..."
)
for prefix in ['.nhr', '.nin', '.nsq']:
[
os.remove(database_path) for database_path in
[s['db'] + prefix for s in self.ctx.anticodons.values()]
if os.path.exists(database_path)
]
# compresssing and decompressing FASTA files changes their hash and make them look like
# modified in git. to avoid that, we will do the database generation in a temporary directory.
temp_dir = filesnpaths.get_temp_directory_path()
self.progress.update("Copying FASTA files to %s ..." % (temp_dir))
# the following line basically returns a dictionary that shows the new path
# of the FASTA file under temp_dir for a given anticodon .. apologies for the
# incomprehensible list comprehension
new_paths = dict([
(os.path.basename(fasta_path),
shutil.copy((fasta_path + '.gz'),
os.path.join(temp_dir,
os.path.basename(fasta_path) + '.gz')))
for fasta_path in [s['db'] for s in self.ctx.anticodons.values()]
])
missing_FASTA_files = [
anticodon for anticodon in self.ctx.anticodons
if not os.path.exists(new_paths[anticodon])
]
if len(missing_FASTA_files):
raise ConfigError(
"Weird news :( Anvi'o is missing some FASTA files that were supposed to be somewhere. Since this "
"can't be your fault, it is not easy to advice what could be the solution to this. If you are not "
"an anvi'o programmer working on this problem this very moment, please get in touch with one."
)
self.progress.update("Decompressing FASTA files in %s" % (temp_dir))
new_paths = dict([(anticodon,
utils.gzip_decompress_file(new_paths[anticodon],
keep_original=False))
for anticodon in new_paths])
for anticodon in self.ctx.anticodons:
self.progress.update("Working on %s in %d threads" %
(anticodon, self.num_threads))
FASTA_file_path_for_anticodon = new_paths[anticodon]
# create a BLAST search database for `FASTA_file_path_for_anticodon`
blast = BLAST(query_fasta=FASTA_file_path_for_anticodon,
run=run_quiet,
progress=progress_quiet,
num_threads=self.num_threads)
blast.log_file_path = os.path.join(
os.path.dirname(FASTA_file_path_for_anticodon),
'%s.log' % anticodon)
blast.makedb(dbtype='nucl')
for prefix in ['.nhr', '.nin', '.nsq']:
if not os.path.exists(FASTA_file_path_for_anticodon + prefix):
raise ConfigError(
"Something went wrong and BLAST did not create the database file it was supposed to "
"for %s :(" % anticodon)
else:
shutil.move(
FASTA_file_path_for_anticodon + prefix,
os.path.dirname(self.ctx.anticodons[anticodon]['db']))
shutil.rmtree(temp_dir)
self.progress.end()
self.run.info_single(
"Every FASTA is now turned into a fancy search database. It means you are now allowed to run "
"`anvi-run-trna-taxonomy` on anvi'o contigs databases. This workflow is very new, and there are "
"caveats to it just like every other computational approach you use to make sense of complex 'omics "
"data. To better understand those caveats you should read our online documentation a bit. If you see "
"things that concerns you, please let anvi'o developers know. They love bad news. If you get good "
"results from this workflow, thank to those who contributed to the GTDB.",
nl_after=1,
mc="green")
def create_search_databases(self):
"""Creates all the search databases"""
self.progress.new("Creating search databases")
self.progress.update(
"Removing any database that still exists in the output directory..."
)
for anticodon_base_path in [
b['db'] for b in self.ctx.anticodons.values()
]:
[
os.remove(f) for f in glob.glob(anticodon_base_path + '.*')
if not f.endswith('.gz')
]
# compresssing and decompressing FASTA files changes their hash and make them look like
# modified in git. to avoid that, we will do the database generation in a temporary directory.
temp_dir = filesnpaths.get_temp_directory_path()
self.progress.update("Copying FASTA files to %s ..." % (temp_dir))
# the following line basically returns a dictionary that shows the new path
# of the FASTA file under temp_dir for a given anticodon .. apologies for the
# incomprehensible list comprehension
new_paths = dict([
(os.path.basename(fasta_path),
shutil.copy((fasta_path + '.gz'),
os.path.join(temp_dir,
os.path.basename(fasta_path) + '.gz')))
for fasta_path in [s['db'] for s in self.ctx.anticodons.values()]
])
missing_FASTA_files = [
anticodon for anticodon in self.ctx.anticodons
if not os.path.exists(new_paths[anticodon])
]
if len(missing_FASTA_files):
raise ConfigError(
"Weird news :( Anvi'o is missing some FASTA files that were supposed to be somewhere. Since this "
"can't be your fault, it is not easy to advice what could be the solution to this. If you are not "
"an anvi'o programmer working on this problem this very moment, please get in touch with one."
)
self.progress.update("Decompressing FASTA files in %s" % (temp_dir))
new_paths = dict([(anticodon,
utils.gzip_decompress_file(new_paths[anticodon],
keep_original=False))
for anticodon in new_paths])
for anticodon in self.ctx.anticodons:
self.progress.update("Working on %s in %d threads" %
(anticodon, self.num_threads))
FASTA_file_path_for_anticodon = new_paths[anticodon]
# create a BLAST search database for `FASTA_file_path_for_anticodon`
blast = BLAST(query_fasta=FASTA_file_path_for_anticodon,
run=run_quiet,
progress=progress_quiet,
num_threads=self.num_threads)
blast.log_file_path = os.path.join(
os.path.dirname(FASTA_file_path_for_anticodon),
'%s.log' % anticodon)
blast.makedb(dbtype='nucl')
files_generated = [
f for f in glob.glob(FASTA_file_path_for_anticodon + '.*')
]
if not len(files_generated):
raise ConfigError(
f"Even though the process to generate BLAST database files for '{anticodon}' has officially ended, "
f"anvi'o is unable to find any files generated by BLAST in the temporary directory it was working "
f"with :( This is as confusing to anvi'o as it probably sounds to you. A likely explanation is that "
f"something went wrong with the `makeblastdb` step. Please go into the following directory, and run "
f"`makeblastdb -in AAA -dbtype nucl; ls AAA*` manually to see what happens: '{temp_dir}'."
)
else:
for file_path in files_generated:
shutil.move(
file_path,
os.path.dirname(self.ctx.anticodons[anticodon]['db']))
shutil.rmtree(temp_dir)
self.progress.end()
self.run.info_single(
"Every FASTA is now turned into a fancy search database. It means you are now allowed to run "
"`anvi-run-trna-taxonomy` on anvi'o contigs databases. This workflow is very new, and there are "
"caveats to it just like every other computational approach you use to make sense of complex 'omics "
"data. To better understand those caveats you should read our online documentation a bit. If you see "
"things that concerns you, please let anvi'o developers know. They love bad news. If you get good "
"results from this workflow, thank to those who contributed to the GTDB.",
nl_after=1,
mc="green")