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clustersAssessment.py
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clustersAssessment.py
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#!/usr/bin/env python2.7
#
# Copyright (C) 2016 INRA
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
__author__ = 'Plateforme bioinformatique Toulouse'
__copyright__ = 'Copyright (C) 2016 INRA'
__license__ = 'GNU General Public License'
__version__ = '1.2.0'
__email__ = 'frogs-support@inrae.fr'
__status__ = 'beta'
import re
import os
import argparse
from frogsSequenceIO import *
from frogsBiom import BiomIO
##################################################################################################################################################
#
# FUNCTIONS
#
##################################################################################################################################################
def samples_from_dir(directory_path, sample_name_sep):
"""
@summary: Parse the directory and return by sample the path to the sequence file.
@param directory_path: [str] Path to the samples directory.
@param sample_name_sep: [str] Separator between sample name and the rest of the filename.
@returns: [dict] By sample name the path of the sequence file.
@warning: The directory must only contains the samples files.
"""
samples = dict()
for filename in os.listdir(directory_path):
if os.path.isfile(os.path.join(directory_path, filename)):
sample_name = filename.split(".")[0].split(sample_name_sep)[0]
samples[sample_name] = os.path.join(directory_path, filename)
return samples
def get_ref_after_simulation(samples):
"""
@summary: Returns the IDs of initial sequences presents after simulation.
@param samples: [dict] By sample name the path of the sequence file
@returns: [list] The first element is a dict of reference present in dataset.
The second element is a dict of reference present by sample.
"""
references = dict()
references_by_sample = dict()
for sample_name in samples:
expected_reference = dict()
FH_sample = SequenceFileReader.factory(samples[sample_name])
for record in FH_sample:
origin = re.search("reference=([^\s]+)", record.description).group(1)
if "," not in origin:
expected_reference[origin] = 1
references[origin] = 1
references_by_sample[sample_name] = expected_reference
FH_sample.close()
return references, references_by_sample
def get_uniq(fasta, references_by_sample):
"""
"""
uniq_id = dict()
uniq_id_by_sample = dict()
# Get sequences
ids_by_sequences = dict()
fh_sequences = FastaIO( fasta )
for record in fh_sequences:
if record.string not in ids_by_sequences:
ids_by_sequences[record.string] = list()
ids_by_sequences[record.string].append( record.id )
fh_sequences.close()
# Get uniq in all dataset
for sequence in ids_by_sequences:
for reference_id in ids_by_sequences[sequence]:
uniq_id[reference_id] = ids_by_sequences[sequence][0]
# Get uniq by sample
for sample_name in references_by_sample:
uniq_id_by_sample[sample_name] = dict()
for reference_id in references_by_sample[sample_name]:
uniq_id_by_sample[sample_name][reference_id] = uniq_id[reference_id]
return uniq_id, uniq_id_by_sample
def get_retrieved_in_dataset(reference_by_obs_id, references, uniq_id):
nb_detected = 0
retrieved = dict()
expected_retrieved = dict()
nb_splits = 0
for obs_id in reference_by_obs_id:
nb_detected += 1
if not "," in reference_by_obs_id[obs_id]: # Is not a chimera
ref_id = reference_by_obs_id[obs_id]
if ref_id in retrieved:
nb_splits += 1
else:
retrieved[ref_id] = 1
if ref_id in references:
expected_retrieved[ref_id] = 1
# Uniq sequence for retrieved
uniq_retrieved = set()
for ref_id in retrieved:
uniq_retrieved.add( uniq_id[ref_id] )
# Add to split the references with the same sequence and retrieved separately
nb_splits += len(retrieved.keys()) - len(uniq_retrieved)
# Uniq sequence for retrieved
uniq_expected_retrieved = set()
for ref_id in expected_retrieved:
uniq_expected_retrieved.add( uniq_id[ref_id] )
# Results
return {
"expected_retrieved": len(uniq_expected_retrieved),
"retrieved": len(uniq_retrieved),
"detected": nb_detected,
"splits": nb_splits
}
def get_retrieved_by_sample( biom_file, reference_by_obs_id, references_by_sample, uniq_id, uniq_id_by_sample ):
counts_by_sample = dict()
biom = BiomIO.from_json( biom_file )
for sample_name in biom.get_samples_names():
nb_detected = 0
retrieved = dict()
expected_retrieved = dict()
for obs in biom.get_observations_by_sample( sample_name ):
nb_detected += 1
if not "," in reference_by_obs_id[obs['id']]: # Is not a chimera
ref_id = reference_by_obs_id[obs['id']]
retrieved[ref_id] = 1
if ref_id in references_by_sample[sample_name]:
expected_retrieved[ref_id] = 1
# Uniq sequence for retrieved
uniq_retrieved = set()
for ref_id in retrieved:
uniq_retrieved.add( uniq_id[ref_id] )
# Uniq sequence for retrieved
uniq_expected_retrieved = set()
for ref_id in expected_retrieved:
uniq_expected_retrieved.add( uniq_id_by_sample[sample_name][ref_id] )
# Results
counts_by_sample[sample_name] = {
"detected": nb_detected,
"retrieved": len(uniq_retrieved),
"expected_retrieved": len(uniq_expected_retrieved)
}
return counts_by_sample
##################################################################################################################################################
#
# MAIN
#
##################################################################################################################################################
if __name__ == "__main__":
# Manage parameters
parser = argparse.ArgumentParser( description='Count by sample # OTU, # real OTU and # real splitted OTU.' )
parser.add_argument( '-v', '--version', action='version', version=__version__ )
parser.add_argument( '-f', '--fasta', required=True, help='Sequences file (format: fasta). ID of the original sequence used to create seed must be in seed description "reference=ID".' )
parser.add_argument( '-b', '--biom', required=True, help='Abundance file (format: BIOM).' )
parser.add_argument( '-o', '--origin', required=True, help='Sequence file provided to the simulation workflow (format: fasta).' )
parser.add_argument( '-r', '--reads-dir', required=True, help='Path to the directory with one sequence file by sample (reads produced by simulation).' )
parser.add_argument( '-s', '--sample-sep', default="_", help='Separator between sample name and the rest of the filename. [Default: _]' )
args = parser.parse_args()
# Get samples files
samples = samples_from_dir(args.reads_dir, args.sample_sep)
# Get expected reference
references, references_by_sample = get_ref_after_simulation(samples)
# Get uniq reference
uniq_id, uniq_id_by_sample = get_uniq(args.origin, references_by_sample)
# Get OTU in results
reference_by_obs_id = dict()
fh_sequences = FastaIO( args.fasta )
for record in fh_sequences:
if ";size=" in record.id:
record.id = record.id.split(";size=", 1)[0]
reference_by_obs_id[record.id] = re.search("reference=([^\s]+)", record.description).group(1)
fh_sequences.close()
counts = get_retrieved_in_dataset( reference_by_obs_id, references, uniq_id )
counts_by_sample = get_retrieved_by_sample( args.biom, reference_by_obs_id, references_by_sample, uniq_id, uniq_id_by_sample )
# Output
print "#After_simu\tDictincts_after_simu\tExpected_retrieved\tRetrieved\tDetected\tSplits"
print "\t".join([ str(len(references)),
str(len(set(uniq_id.values()))),
str(counts["expected_retrieved"]),
str(counts["retrieved"]),
str(counts["detected"]),
str(counts["splits"]) ])
print ""
print "#Sample\tAfter_simu\tDistincts_after_simu\tExpected_retrieved\tRetrieved\tDetected"
for sample in samples:
print "\t".join([ sample,
str(len(references_by_sample[sample])),
str(len(set(uniq_id_by_sample[sample].values()))),
str(counts_by_sample[sample]["expected_retrieved"]),
str(counts_by_sample[sample]["retrieved"]),
str(counts_by_sample[sample]["detected"]) ])