def test_get_reference_sequences(self):
fp = get_reference_sequences()
self.assertIn(
os.path.join('gg_13_8_otus', 'rep_set', '97_otus.fasta'), fp)
self.assertTrue(os.path.isfile(fp))
self.assertTrue(os.path.isabs(fp))
with open(fp, 'rb') as f:
md5 = safe_md5(f).hexdigest()
self.assertEqual(md5, '50b2269712b3738afb41892bed936c29')
def test_get_reference_sequences(self):
fp = get_reference_sequences()
self.assertIn(os.path.join('gg_13_8_otus', 'rep_set', '97_otus.fasta'),
fp)
self.assertTrue(os.path.isfile(fp))
self.assertTrue(os.path.isabs(fp))
with open(fp, 'rb') as f:
md5 = safe_md5(f).hexdigest()
self.assertEqual(md5, '50b2269712b3738afb41892bed936c29')
def get_reference_set():
"""Get the reference set to use for OTU picking
Returns
-------
str
The file path to the reference sequences.
str
The file path to the reference taxonomy.
"""
if ag.is_test_env():
repo = get_repository_dir()
ref_seqs = os.path.join(repo, 'tests/data/otus.fna')
ref_tax = os.path.join(repo, 'tests/data/otus.txt')
return ref_seqs, ref_tax
else:
return qdr.get_reference_sequences(), qdr.get_reference_taxonomy()
def get_reference_set():
"""Get the reference set to use for OTU picking
Returns
-------
str
The file path to the reference sequences.
str
The file path to the reference taxonomy.
"""
if ag.is_test_env():
repo = get_repository_dir()
ref_seqs = os.path.join(repo, 'tests/data/otus.fna')
ref_tax = os.path.join(repo, 'tests/data/otus.txt')
return ref_seqs, ref_tax
else:
return qdr.get_reference_sequences(), qdr.get_reference_taxonomy()
def defineTaxSeqsFile(uploadedSeqsFile):
# uploadSeqsFile(uploadedSeqsFile)
return compareWithDB(uploadedSeqsFile, qdr.get_reference_sequences(),
qdr.get_reference_taxonomy())
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
verbose = opts.verbose
input_fp = opts.input_fp
reference_fp = opts.reference_fp
taxonomy_fp = opts.taxonomy_fp
output_dir = opts.output_dir
verbose = opts.verbose
print_only = opts.print_only
assign_taxonomy = opts.assign_taxonomy
if opts.suppress_taxonomy_assignment:
assign_taxonomy = False
taxonomy_fp = None
parallel = opts.parallel
# No longer checking that jobs_to_start > 2, but
# commenting as we may change our minds about this.
# if parallel: raise_error_on_parallel_unavailable()
if opts.parameter_fp:
try:
parameter_f = open(opts.parameter_fp, 'U')
except IOError:
raise IOError("Can't open parameters file (%s). Does it exist? Do you have read access?"
% opts.parameter_fp)
params = parse_qiime_parameters(parameter_f)
parameter_f.close()
else:
params = parse_qiime_parameters([])
# empty list returns empty defaultdict for now
jobs_to_start = opts.jobs_to_start
default_jobs_to_start = qiime_config['jobs_to_start']
validate_and_set_jobs_to_start(params,
jobs_to_start,
default_jobs_to_start,
parallel,
option_parser)
if print_only:
command_handler = print_commands
else:
command_handler = call_commands_serially
try:
makedirs(output_dir)
except OSError:
if opts.force:
pass
else:
option_parser.error("Output directory already exists. Please choose"
" a different directory, or force overwrite with -f.")
if verbose:
status_update_callback = print_to_stdout
else:
status_update_callback = no_status_updates
run_pick_closed_reference_otus(
input_fp,
reference_fp,
output_dir,
taxonomy_fp,
assign_taxonomy=assign_taxonomy,
command_handler=command_handler,
params=params,
qiime_config=qiime_config,
parallel=parallel,
status_update_callback=status_update_callback)
if get_reference_sequences() == reference_fp:
reference_tree_fp = get_reference_tree()
fn = basename(reference_tree_fp)
copyfile(reference_tree_fp, join(output_dir, fn))
from os.path import basename, join
from qiime_default_reference import (get_reference_sequences,
get_reference_tree)
from qiime.util import (load_qiime_config, parse_command_line_parameters,
get_options_lookup, make_option)
from qiime.parse import parse_qiime_parameters
from qiime.workflow.upstream import run_pick_closed_reference_otus
from qiime.workflow.util import (print_commands, call_commands_serially,
print_to_stdout, no_status_updates, validate_and_set_jobs_to_start)
qiime_config = load_qiime_config()
options_lookup = get_options_lookup()
if get_reference_sequences() == qiime_config['pick_otus_reference_seqs_fp']:
reference_fp_help = (
"The reference sequences [default: %default]. " +
"NOTE: If you do not pass -r to this script, you will be using "
"QIIME's default reference sequences. In this case, QIIME will "
"copy the corresponding reference tree to the output directory. "
"This is the tree that should be used to perform phylogenetic "
"diversity analyses (e.g., with core_diversity_analyses.py).")
else:
reference_fp_help = "The reference sequences [default: %default]."
script_info = {}
script_info[
'brief_description'] = "Closed-reference OTU picking/Shotgun UniFrac workflow."
script_info['script_description'] = """
This script picks OTUs using a closed reference and constructs an OTU table.
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
verbose = opts.verbose
input_fp = opts.input_fp
reference_fp = opts.reference_fp
taxonomy_fp = opts.taxonomy_fp
output_dir = opts.output_dir
verbose = opts.verbose
print_only = opts.print_only
assign_taxonomy = opts.assign_taxonomy
if opts.suppress_taxonomy_assignment:
assign_taxonomy = False
taxonomy_fp = None
parallel = opts.parallel
# No longer checking that jobs_to_start > 2, but
# commenting as we may change our minds about this.
# if parallel: raise_error_on_parallel_unavailable()
if opts.parameter_fp:
try:
parameter_f = open(opts.parameter_fp, 'U')
except IOError:
raise IOError(
"Can't open parameters file (%s). Does it exist? Do you have read access?"
% opts.parameter_fp)
params = parse_qiime_parameters(parameter_f)
parameter_f.close()
else:
params = parse_qiime_parameters([])
# empty list returns empty defaultdict for now
jobs_to_start = opts.jobs_to_start
default_jobs_to_start = qiime_config['jobs_to_start']
validate_and_set_jobs_to_start(params, jobs_to_start,
default_jobs_to_start, parallel,
option_parser)
if print_only:
command_handler = print_commands
else:
command_handler = call_commands_serially
try:
makedirs(output_dir)
except OSError:
if opts.force:
pass
else:
option_parser.error(
"Output directory already exists. Please choose"
" a different directory, or force overwrite with -f.")
if verbose:
status_update_callback = print_to_stdout
else:
status_update_callback = no_status_updates
run_pick_closed_reference_otus(
input_fp,
reference_fp,
output_dir,
taxonomy_fp,
assign_taxonomy=assign_taxonomy,
command_handler=command_handler,
params=params,
qiime_config=qiime_config,
parallel=parallel,
status_update_callback=status_update_callback)
if get_reference_sequences() == reference_fp:
reference_tree_fp = get_reference_tree()
fn = basename(reference_tree_fp)
copyfile(reference_tree_fp, join(output_dir, fn))
from qiime_default_reference import (get_reference_sequences,
get_reference_tree)
from qiime.util import (load_qiime_config, parse_command_line_parameters,
get_options_lookup, make_option)
from qiime.parse import parse_qiime_parameters
from qiime.workflow.upstream import run_pick_closed_reference_otus
from qiime.workflow.util import (print_commands, call_commands_serially,
print_to_stdout, no_status_updates,
validate_and_set_jobs_to_start)
qiime_config = load_qiime_config()
options_lookup = get_options_lookup()
if get_reference_sequences() == qiime_config['pick_otus_reference_seqs_fp']:
reference_fp_help = (
"The reference sequences [default: %default]. " +
"NOTE: If you do not pass -r to this script, you will be using "
"QIIME's default reference sequences. In this case, QIIME will "
"copy the corresponding reference tree to the output directory. "
"This is the tree that should be used to perform phylogenetic "
"diversity analyses (e.g., with core_diversity_analyses.py).")
else:
reference_fp_help = "The reference sequences [default: %default]."
script_info = {}
script_info[
'brief_description'] = "Closed-reference OTU picking/Shotgun UniFrac workflow."
script_info['script_description'] = """
This script picks OTUs using a closed reference and constructs an OTU table.
from qiime_default_reference import get_template_alignment, get_reference_sequences
from skbio import SequenceCollection
gapped_sequences = [
(s.id, str(s)) for s in SequenceCollection.read(get_template_alignment())
][:500]
sequences = [(s.id, str(s))
for s in SequenceCollection.read(get_reference_sequences())][:500]
motif_1 = "GGTGCAAGCCGGTGGAAACA"
def pairwise(l):
res = []
i = iter(l)
for a, b in zip(i, i):
s = min(len(a), len(b))
res.append((a[:s], b[:s]))
return res
from qiime_default_reference import get_template_alignment, get_reference_sequences from skbio import SequenceCollection gapped_sequences = [(s.id, str(s)) for s in SequenceCollection.read(get_template_alignment())][:500] sequences = [(s.id, str(s)) for s in SequenceCollection.read(get_reference_sequences())][:500] motif_1 = "GGTGCAAGCCGGTGGAAACA"
