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#!/usr/bin/env python
# File created on 13 Jul 2012
from __future__ import division
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2011, The QIIME project"
__credits__ = ["Greg Caporaso", "Jose Antonio Navas Molina", "Emily TerAvest"]
__license__ = "GPL"
__version__ = "1.8.0"
__maintainer__ = "Greg Caporaso"
__email__ = "gregcaporaso@gmail.com"
from glob import glob
from os.path import isfile
from qiime.util import parse_command_line_parameters
from qiime.util import make_option
from qiime.beta_diversity import get_phylogenetic_metric
from qiime.beta_diversity import list_known_metrics
from qiime.util import load_qiime_config, get_options_lookup
from qiime.parallel.beta_diversity import (ParallelBetaDiversitySingle,
ParallelBetaDiversityMultiple)
qiime_config = load_qiime_config()
options_lookup = get_options_lookup()
script_info={}
script_info['brief_description']="""Parallel beta diversity"""
script_info['script_description']="""This script performs like the\
beta_diversity.py script, but is intended to make use of\
multicore/multiprocessor environments to perform analyses in parallel."""
script_info['script_usage']=[]
script_info['script_usage'].append(
("""Apply beta_diversity.py in parallel to multiple otu tables""",
"""Apply the unweighted_unifrac and weighted_unifrac metrics (modify with -m)\
to all otu tables in rarefied_otu_tables (-i) and write the resulting output\
files to bdiv/ (-o, will be created if it doesn't exist). Use the rep_set.tre\
(-t) to compute phylogenetic diversity metrics. ALWAYS SPECIFY ABSOLUTE FILE\
PATHS (absolute path represented here as $PWD, but will generally look\
something like /home/ubuntu/my_analysis/).""",
"""%prog -i $PWD/rarefied_otu_tables/ -o $PWD/bdiv/ -t $PWD/rep_set.tre"""))
script_info['script_usage'].append(
("""Apply beta_diversity.py in parallel to a single otu table""",""" """,
"""%prog -i $PWD/otu_table.biom -o $PWD/bdiv_single/ -t $PWD/rep_set.tre"""))
script_info['output_description']="""The output of %prog is a folder containing\
text files, each a distance matrix between samples."""
script_info['required_options'] = [\
make_option('-i', '--input_path',type='existing_path',
help='input path, must be directory [REQUIRED]'),\
make_option('-o', '--output_path',type='new_dirpath',
help='output path, must be directory [REQUIRED]'),
]
script_info['optional_options'] = [
make_option('-m', '--metrics', default='unweighted_unifrac,weighted_unifrac',
type='multiple_choice', mchoices=list_known_metrics(),
help='Beta-diversity metric(s) to use. A comma-separated list should be' +\
' provided when multiple metrics are specified. [default: %default]'),
make_option('-t', '--tree_path', type='existing_filepath',
help='path to newick tree file, required for phylogenetic metrics'+\
' [default: %default]'),\
options_lookup['retain_temp_files'],
options_lookup['suppress_submit_jobs'],
options_lookup['poll_directly'],
options_lookup['cluster_jobs_fp'],
options_lookup['suppress_polling'],
options_lookup['job_prefix'],
options_lookup['seconds_to_sleep'],
options_lookup['jobs_to_start'],
make_option('-f', '--full_tree', action="store_true",
help='By default, each job removes calls _fast_unifrac_setup to remove\
unused parts of the tree. pass -f if you already have a minimal tree, and\
this script will run faster'),
]
script_info['version'] = __version__
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
params = eval(str(opts))
params['metrics'] = ','.join(opts.metrics)
# create local copies of command-line options
input_path = opts.input_path
output_dir = opts.output_path
metrics_list = opts.metrics
tree_fp = opts.tree_path
# Check the tree exists if phylogenetically-aware measure is used
for metric in metrics_list:
try:
metric_f = get_phylogenetic_metric(metric)
if tree_fp == None:
option_parser.error("metric %s requires a tree, but "
"none found" % metric)
except AttributeError:
pass
if isfile(input_path):
# single otu table mode
parallel_runner = ParallelBetaDiversitySingle(
cluster_jobs_fp=opts.cluster_jobs_fp,
jobs_to_start=opts.jobs_to_start,
retain_temp_files=opts.retain_temp_files,
suppress_polling=opts.suppress_polling,
seconds_to_sleep=opts.seconds_to_sleep)
parallel_runner(input_path,
output_dir,
params,
job_prefix=opts.job_prefix,
poll_directly=opts.poll_directly,
suppress_submit_jobs=False)
else:
input_fps = glob('%s/*' % input_path)
parallel_runner = ParallelBetaDiversityMultiple(
cluster_jobs_fp=opts.cluster_jobs_fp,
jobs_to_start=opts.jobs_to_start,
retain_temp_files=opts.retain_temp_files,
suppress_polling=opts.suppress_polling,
seconds_to_sleep=opts.seconds_to_sleep)
parallel_runner(input_fps,
output_dir,
params,
job_prefix=opts.job_prefix,
poll_directly=opts.poll_directly,
suppress_submit_jobs=False)
if __name__ == "__main__":
main()
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