This guide provides a step-by-step guide to:
1) convert BAM files (i.e., public) to paired-end FASTQ files; and
2) run the nextflow nf-core/sarek variant calling pipeline for whole exome sequencing (WES) datasets.
Pre-requisites:
This user guide assumes that you have already installed conda/miniconda3 and nextflow. If you have not done this yet, follow the instructions below:
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qsub -I -S /bin/bash -l walltime=10:00:00 -l select=1:ncpus=2:mem=4gb |
Create a python Python 3.7 environment:
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conda create --name liver python=3.7 |
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To install several tools, prepare a file called environment.yml (example below). Tip: use a text editor (i.e., vim, nano, or other) to copy and paste the code below into the file.
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Move to the folder where all the BAM files are present and prepare the following script (i.e.,launch_BAM2FASTQ.pbs):
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#!/bin/bash -l
#PBS -N BAM2FASTQ
#PBS -l walltime=24:00:00
#PBS -l mem=8gb
#PBS -l ncpus=4
cd $PBS_O_WORKDIR
#activate the conda environment with the necessary tools
conda activate liver
#Sort reads in BAM file by indentifier-name (-n) using 4 CPUs (-@ 4). Note 'prefix' for sorted file noted after $i (input BAM file)
for i in `ls --color=never *.bam`
do
echo $i
samtools sort -@ 4 -n $i ${i%%.bam}_sorted
done
#Extract paired end reads in FASTQ format
for file in `ls --color=never *sorted.bam`
do
echo $file
bedtools bamtofastq -i $file -fq ${file%%.bam}_R1.fastq -fq2 ${file%%.bam}_R2.fastq
#compress FASTQ files to run using the sarek pipeline
gzip -c -9 ${file%%.bam}_R1.fastq > ${file%%.bam}_R1.fastq.gz
gzip -c -9 ${file%%.bam}_R1.fastq > ${file%%.bam}_R2.fastq.gz
done |
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To run Sarek 3 files are required:
launch.pbs → details on how to run the workflow
~/.nextflow/config → specify how to run the workflow in the HPC
samplesheet.csv → provides information on the samples and data to be used (i.e., FASTQ, BAM or CRAM)
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PHASE I - preprocessing
Below is an example of a launch_phase1.pbs file for mapping onto the selected genome:
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#!/bin/bash -l #PBS -N sarek_I #PBS -l walltime=48:00:00 #PBS -l select=1:ncpus=1:mem=5gb cd $PBS_O_WORKDIR NXF_OPTS='-Xms1g -Xmx4g' module load java #specify the nextflow version to use to run the workflow export NXF_VER=22.06.1-edge #run the prepocessing tasks nextflow run nf-core/sarek \ -r 3.1.1 \ -profile singularity \ --genome GATK.GRCh38 \ --input samplesheet.csv |
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singularity {
cacheDir = '$HOME/NXF_SINGULARITY_CACHEDIR'
autoMounts = true
}
conda {
cacheDir = '$HOME/NXF_CONDA_CACHEDIR'
}
singularity {
enabled = true
autoMounts = true
}
process {
executor = 'pbspro'
beforeScript = {
"""
source $HOME/.bashrc
source $HOME/.profile
"""
}
scratch = false
cleanup = false
} |
Example of a samplesheet.csv file:
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patient,sample,lane,fastq_1,fastq_2 healthy_11,1,1,/path/to/data/1.Healthy/Healthy_Combined_11_sorted_R1.fastq.gz,/path/to/data/1.Healthy/Healthy_Combined_11_sorted_R2.fastq.gz |
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Prepare/edit the following launch_phase2.pbs script:
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#!/bin/bash -l #PBS -N sarek_II #PBS -l walltime=48:00:00 #PBS -l select=1:ncpus=1:mem=5gb cd $PBS_O_WORKDIR NXF_OPTS='-Xms1g -Xmx4g' module load java #specify the nextflow version to use to run the workflow export NXF_VER=22.06.1-edge #run the sarek pipeline nextflow run nf-core/sarek \ -r 3.1.1 \ -profile singularity \ --genome GATK.GRCh38 \ --step variant_calling \ --tools haplotypecaller \ --wes \ -resume |
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Prepare/edit the following launch_phase3.pbs script:
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#!/bin/bash -l
#PBS -N sarek_III
#PBS -l walltime=48:00:00
#PBS -l select=1:ncpus=1:mem=5gb
cd $PBS_O_WORKDIR
NXF_OPTS='-Xms1g -Xmx4g'
module load java
#specify the nextflow version to use to run the workflow
export NXF_VER=22.06.1-edge
#run the sarek pipeline
nextflow run nf-core/sarek \
-r 3.1.1 \
-profile singularity \
--genome GATK.GRCh38 \
--step annotate \
--tools vep,snpeff \
--wes \
-resume |
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