#!/usr/bin/env python
"""
This script creates a metadata file in json format
"""
import json
import argparse
import os
import sys
try:
from configparser import ConfigParser
except ImportError:
from ConfigParser import ConfigParser # ver. < 3.0
def parse_options():
"""
parse command line options
"""
parser = argparse.ArgumentParser()
helptext="Root path of input run for which metadata should be created, should contain metadata.tsv and genome_to_id.tsv"
parser.add_argument("-i", "--input-run", type=str, help=helptext)
helptext="output file to write metadata to"
parser.add_argument("-o", "--output", type=str, help=helptext)
helptext="Name of the data set"
parser.add_argument("-n", "--name", type=str, help=helptext)
if not len(sys.argv) > 1:
parser.print_help()
return None
args = parser.parse_args()
return args
def read_metadata(path):
"""
Reads the metadata files for creating some of the mappings
"""
metadata = {}
if not os.path.exists(path):
raise IOError("No such file or directory: %s" % path)
metadata_path = os.path.join(path, "metadata.tsv")
genome_path = os.path.join(path, "genome_to_id.tsv")
with open(metadata_path,'r') as md:
for line in md:
if line.startswith("genome"):
continue
genome, otu, ncbi, novelty = line.strip().split('\t')
metadata[genome] = [otu, ncbi, novelty]
with open(genome_path, 'r') as gid:
for line in gid:
genome, path = line.strip().split('\t')
metadata[genome].append(path)
return metadata
def read_config(path):
"""
Reads the config file used for the creation of the data set
"""
config_path = os.path.join(path, "config.ini")
config = ConfigParser()
config.read(config_path)
return config
def get_sequencing_technology(read_simulator):
"""
Given the read simulator type from the config file, returns the underlying sequencing technology (this has to be edited if new sequencing technologies/reads simulator are added)
"""
dict_of_simulators = {
"art" : "Illumina HiSeq2500",
"wgsim" : "Illumina",
"pbsim" : "Pacific Biosciences",
"nanosim" : "Oxford Nanopore"
}
return dict_of_simulators[read_simulator]
def get_bam_list(path,sample):
bam_path = os.path.join(path,sample,"bam")
bam_files = os.listdir(bam_path)
bam_list = []
for f in bam_files:
if f.endswith(".bam"):
bam_list.append(os.path.join(bam_path,f))
return bam_list
def get_sample_dicts(path):
files = os.listdir(path)
sample_dicts = []
for f in files:
try:
date, time, sample, nr = f.split("_")
except ValueError:
continue
sample_dict = {}
sample_dict["Number"] = nr
sample_dict["Name"] = f
sample_dict["Reads"] = os.path.join(f,"reads","anonymous_reads.fq.gz")
sample_dict["Gold_Standard_Taxonomic_Profile"] = "taxonomic_profile_%s.txt" % nr
sample_dict["Gold_Standard_Assembly"] = os.path.join(f,"contigs","anonymous_gsa.fasta.gz")
sample_dict["Gold_Standard_Read_Binning"] = os.path.join(f,"reads","reads_mapping.tsv.gz")
sample_dict["Gold_Standard_Contig_Binning"] = os.path.join(f,"contigs", "gsa_mapping.tsv.gz")
bam_list = get_bam_list(path,f)
sample_dict["Read_to_genome_mappings"] = bam_list
sample_dicts.append(sample_dict)
return sample_dicts
def list_genomes(metadata):
genome_dicts = []
for genome in metadata: #otu, ncbi, novelty, path
genome_dict = {}
otu, ncbi, novelty, path = metadata[genome]
genome_dict["OTU_Name"] = genome
genome_dict["OTU_NCBI_ID"] = otu
genome_dict["Genome_NCBI_ID"] = ncbi
genome_dict["Novelty_category"] = novelty
genome_dict["Path"] = path
genome_dicts.append(genome_dict)
return genome_dicts
def create_json(path, metadata, config, name):
json = {}
json["Name"] = name
samples = config.get('CommunityDesign', 'number_of_samples')
json["Nr_Samples"] = samples
size = config.get('ReadSimulator', 'size')
json["Total_size_bp"] = float(size) * int(samples)
simulator = config.get('ReadSimulator', 'type')
json["Sequencing_technology"] = get_sequencing_technology(simulator)
if simulator != "art" and simulator != "wgsim": # these use insert sizes
json["Average_read_length_in_bp"] = 150
json["Read_length_standard_deviation_in_bp"] = 0
json["Average_insert_size_in_bp"] = config.get('ReadSimulator', 'fragments_size_mean')
json["Insert_size_standard_deviation_in_bp"] = config.get('ReadSimulator', 'fragment_size_standard_deviation')
else: # these use read sizes
json["Average_read_length_in_bp"] = config.get('ReadSimulator', 'fragments_size_mean')
json["Read_length_standard_deviation_in_bp"] = config.get('ReadSimulator', 'fragment_size_standard_deviation')
json["Average_insert_size_in_bp"] = config.get('ReadSimulator', 'fragments_size_mean')
json["Insert_size_standard_deviation_in_bp"] = config.get('ReadSimulator', 'fragment_size_standard_deviation')
if simulator == "art":
json["Paired-end"] = True
else:
json["Paired-end"] = False
sample_dicts = get_sample_dicts(path)
json["Samples"] = sample_dicts
file_dict = {}
file_dict["Pooled_Gold_Standard_Assembly"] = os.path.join(path, "anonymous_gsa_pooled.fasta.gz")
file_dict["Pooled_Gold_Standard_Binning"] = os.path.join(path, "gsa_pooled_mapping.tsv.gz")
file_dict["Genomes"] = list_genomes(metadata)
file_dict["CAMISIM_config"] = os.path.join(path, "config.ini")
file_dict["CAMISIM_metadata"] = os.path.join(path, "metadata.tsv")
file_dict["CAMISIM_genome_mapping"] = os.path.join(path, "genome_to_id.tsv")
json["Other_files"] = file_dict
return json
def write_json(in_path, out_path, metadata, config, name):
json_path = os.path.join(out_path, "metadata.json")
json_dict = create_json(in_path, metadata, config, name)
json_string = json.dumps(json_dict)
with open(json_path, 'w') as json_file:
json_file.write(json_string)
if __name__ == "__main__":
args = parse_options()
if not args is None:
inpath = args.input_run
outpath = args.output
name = args.name
metadata = read_metadata(inpath)
config = read_config(inpath)
write_json(inpath, outpath, metadata, config, name)
