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Aim:
This pipeline uses raw Oxford Nanopore (ONT) data to run the following processes:
De novo genome assemebly of ONT reads using flye https://github.com/fenderglass/Flye
Sequence comparison of assembled genome to a provide Reference Genome;
Nano-Q: conservatively cleaning ONT reads from bam files and estimate variant frequencies https://github.com/PrestonLeung/Nano-Q
Prerequisites:
Install Nextflow using the following User Guide: Nextflow
Inputs:
ONT raw data in FASTQ format (compressed) - if multiple FASTQ.gz files are available for the same sample all need to be in the same folder. DO NOT place raw files for different samples in the same folder.
Index file that provide information of the ONT data including: Sample ID, location of ONT raw files and a reference genome:
Code Block sampleid,sample_files,reference NC483,/mnt/work/phylo/OxfordNanopore/NC483_barcode96/*.fastq.gz,/mnt/work/phylo/OxfordNanopore/NC483_NC001477_reference_sequence.fasta
The index file (i.e., index.csv) can contain one or multiple samples information, one per line:
| Code Block |
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sampleid,sample_files,reference ET300,/mnt/work/phylo/OxfordNanopore/ET300_barcode95/*.fastq.gz,/mnt/work/phylo/OxfordNanopore/ET300_MT921572_reference_sequence.fasta NC483,/mnt/work/phylo/OxfordNanopore/NC483_barcode96/*.fastq.gz,/mnt/work/phylo/OxfordNanopore/NC483_NC001477_reference_sequence.fasta |
Running the ONTprocessing nextflow pipeline:
Prepare a PBS pro submission script to run the ONTprocessing pipeline. An example launch.pbs script is the following:
| Code Block |
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#!/bin/bash -l #PBS -N ontprocessing #PBS -l select=1:ncpus=2:mem=4gb #PBS -l walltime=24:00:00 #Use the current directory to run the workflow cd $PBS_O_WORKDIR module load java NXF_OPTS='-Xms1g -Xmx4g' nextflow run eresearchqut/ontprocessing --samplesheet index.csv |
Create a folder where you analyses will be run, and place a copy of both launch.pbs and index.csv in the same folder. The submit the job to the HPC cluster:
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Monitor progress of the job:
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qjobs |
Outputs:
Find in a subfolder called ‘work’ all the intermediate files generating while running the ONTprocessing workflow - this folder is not typically used to assess the outputs but rather to debug any issues with the pipeline. Key intermediate files or outputs for specific ‘processes’ (analyses tasks) are saved to a subfolder called ‘results’ where data for the following analyses are presented:
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