#!/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
import os.path
from basic_modules.workflow import Workflow
from utils import logger
from utils import remap
from tool.forge_bsgenome import bsgenomeTool
from tool.bwa_mem_aligner import bwaAlignerMEMTool
from tool.biobambam_filter import biobambam
from tool.idear import idearTool
# ------------------------------------------------------------------------------
[docs]class process_damidseq(Workflow):
"""
Functions for processing Chip-Seq FastQ files. Files are the aligned,
filtered and analysed for peak calling
"""
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 DamID-Seq")
if configuration is None:
configuration = {}
self.configuration.update(configuration)
def _align_filter(self, align_input_files, align_input_file_meta, output_files):
"""
Function for performing the alignment and filtering of fastq files.
"""
output_files_generated = {}
output_metadata_generated = {}
bwa = bwaAlignerMEMTool(self.configuration)
logger.progress("BWA MEM Aligner - " + align_input_files["loc"], status="RUNNING")
bwa_files, bwa_meta = bwa.run(
align_input_files, align_input_file_meta,
{"output": output_files["bam"], "bai": output_files["bai"]}
)
logger.progress("BWA MEM Aligner - " + align_input_files["loc"], status="DONE")
try:
output_files_generated["bam"] = bwa_files["bam"]
output_metadata_generated["bam"] = bwa_meta["bam"]
tool_name = output_metadata_generated["bam"].meta_data["tool"]
output_metadata_generated["bam"].meta_data["tool_description"] = tool_name
output_metadata_generated["bam"].meta_data["tool"] = "process_damidseq"
output_files_generated["bai"] = bwa_files["bai"]
output_metadata_generated["bai"] = bwa_meta["bai"]
tool_name = output_metadata_generated["bai"].meta_data["tool"]
output_metadata_generated["bai"].meta_data["tool_description"] = tool_name
output_metadata_generated["bai"].meta_data["tool"] = "process_damidseq"
except KeyError as msg:
logger.fatal(
"KeyError error - BWA aligner failed: {0}\n{1}\n{2}\n{3}".format(
msg, output_files_generated["bam"],
"Available file keys: " + ", ".join(bwa_files.keys()),
"Available mets keys: " + ", ".join(bwa_meta.keys())
)
)
return {}, {}
# Filter the bams
b3f = biobambam(self.configuration)
logger.progress("BioBamBam Filtering - " + align_input_files["loc"], status="RUNNING")
b3f_files, b3f_meta = b3f.run(
{"input": bwa_files["bam"]},
{"input": bwa_meta["bam"]},
{"output": output_files["bam_filtered"], "bai": output_files["bai_filtered"]}
)
logger.progress("BioBamBam Filtering - " + align_input_files["loc"], status="DONE")
try:
output_files_generated["bam_filtered"] = b3f_files["bam"]
output_metadata_generated["bam_filtered"] = b3f_meta["bam"]
tool_name = output_metadata_generated["bam_filtered"].meta_data["tool"]
output_metadata_generated["bam_filtered"].meta_data["tool_description"] = tool_name
output_metadata_generated["bam_filtered"].meta_data["tool"] = "process_damidseq"
output_files_generated["bai_filtered"] = b3f_files["bai"]
output_metadata_generated["bai_filtered"] = b3f_meta["bai"]
tool_name = output_metadata_generated["bai_filtered"].meta_data["tool"]
output_metadata_generated["bai_filtered"].meta_data["tool_description"] = tool_name
output_metadata_generated["bai_filtered"].meta_data["tool"] = "process_damidseq"
except KeyError as msg:
logger.fatal("KeyError error - BioBamBam filtering failed: {0}\n{1}".format(
msg, output_files_generated["bam_filtered"]))
return {}, {}
return (output_files_generated, output_metadata_generated)
[docs] def run(self, input_files, metadata, output_files):
"""
Main run function for processing DamID-seq FastQ data. Pipeline aligns
the FASTQ files to the genome using BWA. iDEAR is then used for peak
calling to identify transcription factor binding sites within the
genome.
Currently this can only handle a single data file and a single
background file.
Parameters
----------
input_files : dict
Location of the initial input files required by the workflow
genome : str
Genome FASTA file
index : str
Location of the BWA archived index files
fastq_1 : str
Location of the FASTQ reads files
fastq_2 : str
Location of the FASTQ repeat reads files
bg_fastq_1 : str
Location of the background FASTQ reads files
bg_fastq_2 : str
Location of the background FASTQ repeat reads files
metadata : dict
Input file meta data associated with their roles
genome : str
index : str
fastq_1 : str
fastq_2 : str
bg_fastq_1 : str
bg_fastq_2 : str
output_files : dict
Output file locations
bam [, "bam_bg"] : str
filtered [, "filtered_bg"] : str
Returns
-------
output_files : dict
Output file locations associated with their roles, for the output
bam [, "bam_bg"] : str
Aligned FASTQ short read file [ and aligned background file]
locations
filtered [, "filtered_bg"] : str
Filtered versions of the respective bam files
bigwig : str
Location of the bigwig peaks
output_metadata : dict
Output metadata for the associated files in output_files
bam [, "bam_bg"] : Metadata
filtered [, "filtered_bg"] : Metadata
bigwig : Metadata
"""
output_files_generated = {
"bam": [],
"bam_filtered": []
}
output_metadata = {
"bam": [],
"bam_filtered": []
}
# BSgenome
logger.info("Generating BSgenome")
if "genome_public" in input_files:
genome_input_file = {"genome": input_files["genome_public"]}
genome_input_meta = {"genome": metadata["genome_public"]}
else:
genome_input_file = {"genome": input_files["genome"]}
genome_input_meta = {"genome": metadata["genome"]}
bsg = bsgenomeTool(self.configuration)
logger.progress("BSgenome Indexer", status="RUNNING")
bsgi, bsgm = bsg.run(
genome_input_file,
genome_input_meta,
{
"bsgenome": output_files["bsgenome"],
"chrom_size": output_files["chrom_size"],
"genome_2bit": output_files["genome_2bit"],
"seed_file": output_files["seed_file"]
}
)
logger.progress("BSgenome Indexer", status="DONE")
try:
file_keys = ["bsgenome", "chrom_size", "genome_2bit", "seed_file"]
for file_key in file_keys:
output_files_generated[file_key] = bsgi[file_key]
output_metadata[file_key] = bsgm[file_key]
tool_name = output_metadata[file_key].meta_data['tool']
output_metadata[file_key].meta_data['tool_description'] = tool_name
output_metadata[file_key].meta_data['tool'] = "process_damidseq"
except KeyError:
logger.fatal("BSgenome indexer failed")
return {}, {}
# Align and filter reads
for prefix in ["", "bg_"]:
for i, aln in enumerate(input_files[prefix + "fastq_1"]):
logger.info("BWA MEM Aligning and filtering of " + aln)
if "genome_public" in input_files:
align_input_files = remap(
input_files, genome="genome_public", index="index_public",
loc=input_files[prefix + "fastq_1"][i])
align_input_file_meta = remap(
metadata, genome="genome_public", index="index_public",
loc=input_files[prefix + "fastq_1"][i])
else:
align_input_files = remap(
input_files, genome="genome", index="index",
loc=input_files[prefix + "fastq_1"][i])
align_input_file_meta = remap(
metadata, genome="genome", index="index",
loc=input_files[prefix + "fastq_1"][i])
if prefix + "fastq_2" in input_files:
align_input_files["fastq_2"] = input_files[prefix + "fastq_2"][i]
align_input_file_meta["fastq_2"] = metadata[prefix + "fastq_2"][i]
fastq_in = os.path.split(input_files[prefix + "fastq_1"][i])
fastq_suffix = fastq_in[1].split(".")[-1]
align_output_files = {
"bam": os.path.join(
self.configuration["execution"],
fastq_in[1].replace(fastq_suffix, "bam")
),
"bam_filtered": os.path.join(
self.configuration["execution"],
fastq_in[1].replace(fastq_suffix, "filtered.bam")
),
"bai": os.path.join(
self.configuration["execution"],
fastq_in[1].replace(fastq_suffix, "bai")
),
"bai_filtered": os.path.join(
self.configuration["execution"],
fastq_in[1].replace(fastq_suffix, "filtered.bai")
)
}
bwa_files, bwa_meta = self._align_filter(
align_input_files, align_input_file_meta, align_output_files)
try:
output_files_generated[prefix + "bam"].append(bwa_files["bam"])
output_metadata[prefix + "bam"].append(bwa_meta["bam"])
output_files_generated[prefix + "bam_filtered"].append(
bwa_files["bam_filtered"])
output_metadata[prefix + "bam_filtered"].append(bwa_meta["bam"])
output_files_generated[prefix + "bai"].append(bwa_files["bai"])
output_metadata[prefix + "bai"].append(bwa_meta["bai"])
output_files_generated[prefix + "bai_filtered"].append(
bwa_files["bai_filtered"])
output_metadata[prefix + "bai_filtered"].append(bwa_meta["bai"])
except KeyError as msg:
logger.fatal("Error aligning and filtering input FASTQ files")
return {}, {}
# iDEAR to call peaks
idear_caller = idearTool(self.configuration)
logger.progress("iDEAR Peak Caller", status="RUNNING")
idear_files, idear_meta = idear_caller.run(
{
"bam": output_files_generated["bam_filtered"],
"bg_bam": output_files_generated["bg_bam_filtered"],
"bsgenome": input_files["bsgenome"]
}, {
"bam": output_metadata["bam_filtered"],
"bg_bam": output_metadata["bg_bam_filtered"],
"bsgenome": metadata["bsgenome"]
}, {
"bigwig": output_files["bigwig"],
}
)
logger.progress("iDEAR Peak Caller", status="DONE")
try:
output_files_generated["bigwig"] = idear_files["bigwig"]
output_metadata["bigwig"] = idear_meta["bigwig"]
tool_name = output_metadata["bigwig"].meta_data["tool"]
output_metadata["bigwig"].meta_data["tool_description"] = tool_name
output_metadata["bigwig"].meta_data["tool"] = "process_damidseq"
except KeyError as msg:
logger.fatal("KeyError error - iDEAR filtering failed: {0}\n{1}".format(
msg, "bigwig"))
return {}, {}
return output_files_generated, 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_damidseq,
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="iDamID-seq peak calling")
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)