def process_kegg_db(output_dir,
kegg_loc,
gene_ko_link_loc=None,
download_date=None,
threads=10,
verbose=True):
if download_date is None:
download_date = get_iso_date()
if gene_ko_link_loc is not None:
# add KOs to end of header where KO is not already there
kegg_mod_loc = path.join(output_dir, 'kegg.mod.fa')
write_sequence(generate_modified_kegg_fasta(kegg_loc,
gene_ko_link_loc),
format='fasta',
into=kegg_mod_loc)
else:
kegg_mod_loc = kegg_loc
# make mmseqsdb from modified kegg fasta
kegg_mmseqs_db = path.join(output_dir, 'kegg.%s.mmsdb' % download_date)
make_mmseqs_db(kegg_mod_loc,
kegg_mmseqs_db,
create_index=True,
threads=threads,
verbose=verbose)
return kegg_mmseqs_db
def download_and_process_viral_refseq(merged_viral_faas=None,
output_dir='.',
viral_files=2,
threads=10,
verbose=True):
"""Can only download newest version"""
# download all of the viral protein files, need to know the number of files
# TODO: Make it so that you don't need to know number of viral files in refseq viral
if merged_viral_faas is None: # download database if not provided
faa_base_name = 'viral.%s.protein.faa.gz'
viral_faa_glob = path.join(output_dir, faa_base_name % '*')
for number in range(viral_files):
number += 1
refseq_url = 'ftp://ftp.ncbi.nlm.nih.gov/refseq/release/viral/viral.%s.protein.faa.gz' % number
refseq_faa = path.join(output_dir, faa_base_name % number)
download_file(refseq_url, refseq_faa, verbose=verbose)
# then merge files from above
merged_viral_faas = path.join(output_dir,
'viral.merged.protein.faa.gz')
run_process([
'cat %s > %s' % (' '.join(glob(viral_faa_glob)), merged_viral_faas)
],
shell=True)
# make mmseqs database
refseq_viral_mmseqs_db = path.join(
output_dir, 'refseq_viral.%s.mmsdb' % get_iso_date())
make_mmseqs_db(merged_viral_faas,
refseq_viral_mmseqs_db,
create_index=True,
threads=threads,
verbose=verbose)
return refseq_viral_mmseqs_db
def download_and_process_merops_peptidases(peptidase_faa=None,
output_dir='.',
threads=10,
verbose=True):
if peptidase_faa is None: # download database if not provided
peptidase_faa = path.join(output_dir, 'merops_peptidases_nr.faa')
merops_url = 'ftp://ftp.ebi.ac.uk/pub/databases/merops/current_release/pepunit.lib'
download_file(merops_url, peptidase_faa, verbose=verbose)
peptidase_mmseqs_db = path.join(output_dir,
'peptidases.%s.mmsdb' % get_iso_date())
make_mmseqs_db(peptidase_faa,
peptidase_mmseqs_db,
create_index=True,
threads=threads,
verbose=verbose)
return peptidase_mmseqs_db
def download_and_process_uniref(uniref_fasta_zipped=None,
output_dir='.',
uniref_version='90',
threads=10,
verbose=True):
""""""
if uniref_fasta_zipped is None: # download database if not provided
uniref_fasta_zipped = path.join(output_dir,
'uniref%s.fasta.gz' % uniref_version)
uniref_url = 'ftp://ftp.uniprot.org/pub/databases/uniprot/uniref/uniref%s/uniref%s.fasta.gz' % \
(uniref_version, uniref_version)
download_file(uniref_url, uniref_fasta_zipped, verbose=verbose)
uniref_mmseqs_db = path.join(
output_dir, 'uniref%s.%s.mmsdb' % (uniref_version, get_iso_date()))
make_mmseqs_db(uniref_fasta_zipped,
uniref_mmseqs_db,
create_index=True,
threads=threads,
verbose=verbose)
return uniref_mmseqs_db
def test_make_mmseqs_db(mmseqs_db_dir):
faa_path = os.path.join('tests', 'data', 'NC_001422.faa')
output_file = str(mmseqs_db_dir.join('mmseqs_db.mmsdb'))
make_mmseqs_db(faa_path, output_file, True, 1)
assert os.path.isfile(output_file)
def target_mmseqs_db(mmseqs_db_dir, phix_proteins):
output_file = str(mmseqs_db_dir.join('target.mmsdb'))
make_mmseqs_db(phix_proteins, output_file, True, 1)
return output_file
def mmseqs_db(prodigal_faa, mmseqs_db_dir):
output_file = str(mmseqs_db_dir.join('mmseqs_db.mmsdb'))
make_mmseqs_db(prodigal_faa, output_file, True, 1)
return output_file
