#!/usr/bin/env python
"""
.. See the NOTICE file distributed with this work for additional information
regarding copyright ownership.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from __future__ import print_function
import argparse
from basic_modules.workflow import Workflow
from utils import logger
from tool.trimgalore import trimgalore
# ------------------------------------------------------------------------------
[docs]class process_trim_galore(Workflow): # pylint: disable=invalid-name,too-few-public-methods
"""
Functions for filtering FASTQ files.
Files are filtered for removal of duplicate reads.
Low quality reads in qseq file can also be filtered.
"""
def __init__(self, configuration=None):
"""
Initialise the class
Parameters
----------
configuration : dict
a dictionary containing parameters that define how the operation
should be carried out, which are specific to each Tool.
"""
logger.info("Processing trim galore")
if configuration is None:
configuration = {}
self.configuration.update(configuration)
[docs] def run(self, input_files, metadata, output_files):
"""
This pipeline processes FASTQ files to trim low quality base calls and
adapter sequences
Parameters
----------
input_files : dict
List of strings for the locations of files. These should include:
fastq : str
Location for the first FASTQ file for single or paired end reads
metadata : dict
Input file meta data associated with their roles
output_files : dict
fastq_trimmed : str
Returns
-------
fastq_trimmed|fastq_trimmed : str
Locations of the filtered FASTQ files from which trimmings were made
"""
output_results_files = {}
output_metadata = {}
logger.info("trim_galore")
trimg = trimgalore(self.configuration)
logger.progress("TrimGalore", status="RUNNING")
if "fastq2" in input_files:
trim_files, trim_meta = trimg.run(
{
"fastq1": input_files["fastq1"],
"fastq2": input_files["fastq2"]
},
{
"fastq1": metadata["fastq1"],
"fastq2": metadata["fastq2"]
},
{
"fastq1_trimmed": output_files["fastq1_trimmed"],
"fastq2_trimmed": output_files["fastq2_trimmed"],
"fastq1_report": output_files["fastq1_report"],
"fastq2_report": output_files["fastq2_report"]
}
)
try:
output_results_files["fastq2_trimmed"] = trim_files["fastq2_trimmed"]
output_metadata["fastq2_trimmed"] = trim_meta["fastq2_trimmed"]
tool_name = output_metadata["fastq2_trimmed"].meta_data["tool"]
output_metadata["fastq2_trimmed"].meta_data["tool_description"] = tool_name
output_metadata["fastq2_trimmed"].meta_data["tool"] = "process_trim_galore"
output_results_files["fastq2_report"] = trim_files["fastq2_report"]
output_metadata["fastq2_report"] = trim_meta["fastq2_report"]
tool_name = output_metadata["fastq2_report"].meta_data["tool"]
output_metadata["fastq2_report"].meta_data["tool_description"] = tool_name
output_metadata["fastq2_report"].meta_data["tool"] = "process_trim_galore"
except KeyError:
logger.fatal("Trim Galore fastq2: Error while trimming")
return {}, {}
else:
trim_files, trim_meta = trimg.run(
{"fastq1": input_files["fastq1"]},
{"fastq1": metadata["fastq1"]},
{
"fastq1_trimmed": output_files["fastq1_trimmed"],
"fastq1_report": output_files["fastq1_report"]
}
)
logger.progress("TrimGalore", status="DONE")
try:
output_results_files["fastq1_trimmed"] = trim_files["fastq1_trimmed"]
output_metadata["fastq1_trimmed"] = trim_meta["fastq1_trimmed"]
tool_name = output_metadata["fastq1_trimmed"].meta_data["tool"]
output_metadata["fastq1_trimmed"].meta_data["tool_description"] = tool_name
output_metadata["fastq1_trimmed"].meta_data["tool"] = "process_trim_galore"
output_results_files["fastq1_report"] = trim_files["fastq1_report"]
output_metadata["fastq1_report"] = trim_meta["fastq1_report"]
tool_name = output_metadata["fastq1_report"].meta_data["tool"]
output_metadata["fastq1_report"].meta_data["tool_description"] = tool_name
output_metadata["fastq1_report"].meta_data["tool"] = "process_trim_galore"
except KeyError:
logger.fatal("Trim Galore fastq1: Error while trimming")
return {}, {}
return (output_results_files, output_metadata)
# ------------------------------------------------------------------------------
def main_json(config, in_metadata, out_metadata):
"""
Alternative main function
-------------
This function launches the app using configuration written in
two json files: config.json and input_metadata.json.
"""
# 1. Instantiate and launch the App
print("1. Instantiate and launch the App")
from apps.jsonapp import JSONApp
app = JSONApp()
result = app.launch(process_trim_galore,
config,
in_metadata,
out_metadata)
# 2. The App has finished
print("2. Execution finished; see " + out_metadata)
print(result)
return result
# ------------------------------------------------------------------------------
if __name__ == "__main__":
# Set up the command line parameters
PARSER = argparse.ArgumentParser(description="Trim galore")
PARSER.add_argument("--config", help="Configuration file")
PARSER.add_argument("--in_metadata", help="Location of input metadata file")
PARSER.add_argument("--out_metadata", help="Location of output metadata file")
PARSER.add_argument("--local", action="store_const", const=True, default=False)
# Get the matching parameters from the command line
ARGS = PARSER.parse_args()
CONFIG = ARGS.config
IN_METADATA = ARGS.in_metadata
OUT_METADATA = ARGS.out_metadata
LOCAL = ARGS.local
if LOCAL:
import sys
sys._run_from_cmdl = True # pylint: disable=protected-access
RESULTS = main_json(CONFIG, IN_METADATA, OUT_METADATA)
print(RESULTS)