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root-dax.py
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#!/usr/bin/env python
'''
NOTE:
- Comment out NCBI Download (sra_run) dependency line at the end if local Illumina sequences are used.
'''
import sys
import os
# Import the Python DAX library
os.sys.path.insert(0, "/util/opt/pegasus-wms/5.0/lib64/pegasus/externals/python/")
from Pegasus.DAX3 import *
dax = ADAG("pipeline")
base_dir = os.getcwd()
run_dir = sys.argv[1]
sra_run = []
trim_run = []
fastqc_run = []
spades_run = []
quast_run = []
filtering_run = []
prokka_run = []
plasmidfinder_run = []
forward_file = []
reverse_file = []
list_of_fastqc_files = []
list_of_gff_files = []
list_of_contig_files = []
list_of_filtererd_sra_ids = []
# Open input list and count files
input_file = open("sra_ids.txt")
lines = input_file.readlines()
input_file = open("sra_ids.txt")
length = len(input_file.readlines())
# Add file executable and job for sub-pipeline
c = File("sub-pipeline.dax")
# Add file for conda environment
conda_file = File("prokevo.yml")
# Add a job to analyze the output of split and generate a sub dax with correct number of parallelism based on output of previous job
generate = Job("ex_generate")
generate.addArguments(run_dir)
generate.setStdout("sub-pipeline.dax")
generate.addProfile(Profile(namespace="env",key="PYTHONPATH",value=os.environ['PYTHONPATH']))
generate.addProfile(Profile(namespace="hints",key="execution.site",value="local"))
generate.uses(c, link=Link.OUTPUT)
dax.addJob(generate)
# Add a subdax job of type DAX that takes the runtime generated sub dax file in the previous step and runs the computation.
sub_dax = DAX(c)
sub_dax.addArguments("--sites local-hcc","--output-site local-hcc","--basename sub-pipeline")
dax.addJob(sub_dax)
# Start analysis
# add job to create conda environment
conda_run = Job("ex_conda_run")
conda_run.addArguments(conda_file)
conda_run.uses(conda_file, link=Link.INPUT)
dax.addJob(conda_run)
for i in range(0,length):
srr_id = lines[i].strip()
forward_file.append(File(str(srr_id) + "_1.fastq"))
reverse_file.append(File(str(srr_id) + "_2.fastq"))
dax.addFile(forward_file[i])
dax.addFile(reverse_file[i])
# add job for downloading data from NCBI
sra_run.append(Job("ex_sra_run"))
sra_run[i].addArguments(str(srr_id))
sra_run[i].uses(forward_file[i], link=Link.OUTPUT, transfer=False)
sra_run[i].uses(reverse_file[i], link=Link.OUTPUT, transfer=False)
# add profile for download limit
# Profile(PROPERTY_KEY[0], PROFILE KEY, PROPERTY_KEY[1])
sra_run[i].addProfile(Profile("dagman", "CATEGORY", "sradownload"))
# sra_run[i].addProfile(Profile("pegasus", "label", str(srr_id)))
dax.addJob(sra_run[i])
# add job for Trimmomatic
trim_run.append(Job("ex_trim_run"))
trim_run[i].addArguments(forward_file[i].name, reverse_file[i].name, str(srr_id) + "_pair_1_trimmed.fastq", str(srr_id) + "_unpair_1_trimmed.fastq", str(srr_id) + "_pair_2_trimmed.fastq", str(srr_id) + "_unpair_2_trimmed.fastq")
trim_run[i].uses(forward_file[i], link=Link.INPUT)
trim_run[i].uses(reverse_file[i], link=Link.INPUT)
trim_run[i].uses(str(srr_id) + "_pair_1_trimmed.fastq", link=Link.OUTPUT, transfer=False)
trim_run[i].uses(str(srr_id) + "_unpair_1_trimmed.fastq", link=Link.OUTPUT, transfer=False)
trim_run[i].uses(str(srr_id) + "_pair_2_trimmed.fastq", link=Link.OUTPUT, transfer=False)
trim_run[i].uses(str(srr_id) + "_unpair_2_trimmed.fastq", link=Link.OUTPUT, transfer=False)
# trim_run[i].addProfile(Profile("pegasus", "label", str(srr_id)))
dax.addJob(trim_run[i])
# add job for FastQC
fastqc_run.append(Job("ex_fastqc_run"))
fastqc_run[i].addArguments(str(srr_id) + "_pair_1_trimmed.fastq", str(srr_id) + "_pair_2_trimmed.fastq")
fastqc_run[i].uses(str(srr_id) + "_pair_1_trimmed.fastq", link=Link.INPUT)
fastqc_run[i].uses(str(srr_id) + "_pair_2_trimmed.fastq", link=Link.INPUT)
fastqc_run[i].uses(str(srr_id) + "_pair_1_trimmed_fastqc/summary.txt", link=Link.OUTPUT, transfer=False)
fastqc_run[i].uses(str(srr_id) + "_pair_2_trimmed_fastqc/summary.txt", link=Link.OUTPUT, transfer=False)
dax.addJob(fastqc_run[i])
# add files
f1 = File(str(srr_id) + "_pair_1_trimmed_fastqc/summary.txt")
f2 = File(str(srr_id) + "_pair_2_trimmed_fastqc/summary.txt")
list_of_fastqc_files.append(f1)
list_of_fastqc_files.append(f2)
# add job for Spades
spades_run.append(Job("ex_spades_run"))
spades_run[i].addArguments(str(srr_id) + "_pair_1_trimmed.fastq", str(srr_id) + "_pair_2_trimmed.fastq", str(srr_id) + "_spades_output")
spades_run[i].uses(str(srr_id) + "_pair_1_trimmed.fastq", link=Link.INPUT)
spades_run[i].uses(str(srr_id) + "_pair_2_trimmed.fastq", link=Link.INPUT)
spades_run[i].uses(str(srr_id) + "_spades_output/contigs.fasta", link=Link.OUTPUT)
spades_run[i].addProfile(Profile("pegasus", "runtime", "3600"))
spades_run[i].addProfile(Profile("globus", "maxwalltime", "600"))
# spades_run[i].addProfile(Profile("pegasus", "label", str(srr_id)))
dax.addJob(spades_run[i])
# add job for Quast
quast_run.append(Job("ex_quast_run"))
quast_run[i].addArguments(str(srr_id) + "_quast_output", str(srr_id) + "_spades_output/contigs.fasta")
quast_run[i].uses(str(srr_id) + "_spades_output/contigs.fasta", link=Link.INPUT)
quast_run[i].uses(str(srr_id) + "_quast_output/transposed_report.tsv", link=Link.OUTPUT)
# quast_run[i].addProfile(Profile("pegasus", "label", str(srr_id)))
dax.addJob(quast_run[i])
# add job for Filterig contigs
filtering_run.append(Job("ex_filtering_run"))
filtering_run[i].addArguments(str(srr_id) + "_quast_output/transposed_report.tsv", str(srr_id) + "_spades_output/contigs.fasta", run_dir, str(srr_id))
filtering_run[i].uses(str(srr_id) + "_quast_output/transposed_report.tsv", link=Link.INPUT)
filtering_run[i].uses(str(srr_id) + "_spades_output/contigs.fasta", link=Link.INPUT)
# filtering_run[i].addProfile(Profile("pegasus", "label", str(srr_id)))
dax.addJob(filtering_run[i])
# add job for cat FastQC Fail
ex_cat = Executable(namespace="dax", name="cat", version="4.0", os="linux", arch="x86_64", installed=True)
ex_cat.addPFN(PFN("/bin/cat", "local-hcc"))
dax.addExecutable(ex_cat)
output_fastqc_cat = File("fastqc_summary_all.txt")
cat = Job(namespace="dax", name=ex_cat)
cat.addArguments(*list_of_fastqc_files)
for l in list_of_fastqc_files:
cat.uses(l, link=Link.INPUT)
cat.setStdout(output_fastqc_cat)
cat.uses(output_fastqc_cat, link=Link.OUTPUT, transfer=True, register=False)
dax.addJob(cat)
# add job for FastQC Fail
output_fastqc_fail = File("fastqc_summary_final.txt")
fastqc_fail_run = Job("ex_fastqc_fail_run")
fastqc_fail_run.addArguments(output_fastqc_cat, output_fastqc_fail)
fastqc_fail_run.uses(output_fastqc_cat, link=Link.INPUT)
fastqc_fail_run.uses(output_fastqc_fail, link=Link.OUTPUT, transfer=True)
dax.addJob(fastqc_fail_run)
input_file = open("sra_ids.txt")
length = len(input_file.readlines())
for i in range(0,length):
# Add control-flow dependencies
# dax.addDependency(Dependency(parent=conda_run, child=trim_run[i]))
# USE THE LINE ABOVE AND COMMENT OUT THE 2 LINES BELOW TO SKIP NCBI DOWNLOAD!!!
dax.addDependency(Dependency(parent=conda_run, child=sra_run[i]))
dax.addDependency(Dependency(parent=sra_run[i], child=trim_run[i]))
dax.addDependency(Dependency(parent=trim_run[i], child=fastqc_run[i]))
dax.addDependency(Dependency(parent=fastqc_run[i], child=cat))
dax.addDependency(Dependency(parent=trim_run[i], child=spades_run[i]))
dax.addDependency(Dependency(parent=spades_run[i], child=quast_run[i]))
dax.addDependency(Dependency(parent=quast_run[i], child=filtering_run[i]))
dax.addDependency(Dependency(parent=filtering_run[i], child=generate))
dax.addDependency(Dependency(parent=cat, child=fastqc_fail_run))
dax.addDependency(Dependency(parent=generate, child=sub_dax))
# Write the DAX to stdout
dax.writeXML(sys.stdout)