This guide provides a step-by-step guide to 1) convert BAM files (i.e., public) to FASTQ; and 2) run the nextflow nf-core/sarek variant calling pipeline.
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conda activate liver |
Prepare a file called environment.yml - 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 |
Submit the job to the PBS scehduler:
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Check the submited job(s):
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qjobs |
Sarek
Create a conda environment with nf-core
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conda create --name nf-core python=3.8 nf-core nextflow
conda activate nf-core |
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nf-core download sarek -r 3.1.2 --output nf-core-sarek -x nonce -c none |