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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:

• Conda installation: https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.

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• html

• Code Block
  wget https://repo.anaconda.com/miniconda/Miniconda3-py37_22.11.1-1-Linux-x86_64.sh bash Miniconda3-py37_22.11.1-1-Linux-x86_64.sh

• nextflow installation: Nextflow

• VCFtools: https://vcftools.github.io/man_latest.html

Create a Conda environment with tools needed for downstream

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analyses

Log into the HPC using your user credentials. To install tools, we will use an interactive PBS session:

qsub -I -S /bin/bash -l walltime=10:00:00 -l select=1:ncpus=2:mem=4gb

Create a python Python 3.7 environment:

conda create --name liver python=3.7

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conda activate liver

Prepare Then you can install one tool at a time or provide a list (see below); however, installing a list of tools may take a while.

We will use samtools and bcftools for the first part of the tutorial. Run the following commands:

conda install -c bioconda samtools

conda install -c bioconda bedtools

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.

channels:
  - bioconda
  - conda-forge
dependencies:
  - bedtoolsseqkit
  - samtoolsvcftools
  - seqkitbcftools
  - vcftools
  - emboss

Run the following command to install additional tools

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conda deactivate

Convert BAM to FASTQ

Move to the folder where all the BAM files are present and prepare the following script (i.e.,launch_BAM2FASTQ.pbs):

#!/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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Check the submitted job(s):

qjobs

Run variant calling using the nextflow nf-core/sarek pipeline

source: https://nf-co.re/sarek/3.1.2

To run Sarek 3 files are required:

1. launch.pbs → details on how to run the workflow

2. ~/.nextflow/config → specify how to run the workflow in the HPC

3. 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, mapping, markduplicates, recalibrate

• Phase II: Variant calling

• Phase III: Annotation

PHASE I - preprocessing

Below is an example of a launch_phase1.pbs file for mapping onto the selected genome:

#!/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

~/.nextflow/config file: (Note: You may already have this file if you installed Nextflow using this guide )

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:

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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qsub launch_phase1.pbs

PHASE II - variant calling

Prepare/edit the following launch_phase2.pbs script:

#!/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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Alternatively, view the progress of the submitted job on the Nextflow Tower.

PHASE III - annotation

Download the singularity container for VEP in your catched Nextflow Singularity folder

singularity pull  --name nfcore-vep-106.1.GRCh38.img docker://nfcore/vep:106.1.GRCh38

Prepare/edit the following launch_phase3.pbs script:

#!/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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