Overview

The MSU HPCC, managed by ICER, provides a robust platform for running bioinformatics pipelines. This guide details how to run the nf-core/sarek pipeline for whole genome sequencing (WGS) analysis, ensuring efficient and reproducible workflows.

Key Benefits of nf-core/sarek

nf-core/sarek offers:

• Reproducible WGS Analysis: Supports germline and somatic variant calling.
• Portability: Runs seamlessly across various computing infrastructures.
• Scalability: Handles both small-scale and large-scale WGS datasets.

Prerequisites

• Access to MSU HPCC with a valid ICER account.
• Basic understanding of Singularity and Nextflow.

Step-by-Step Tutorial

Note on Directory Variables

On the MSU HPCC:

• $HOME refers to the user’s home directory (/mnt/home/username).
• $SCRATCH refers to the user’s scratch directory, ideal for temporary files and large data processing.

Note on Working Directory

The working directory, where intermediate and temporary files are stored, can be specified using the -w flag when running the pipeline. This keeps outputs and temporary data organized.

1. Load Nextflow Module

Ensure Nextflow is loaded:

module load Nextflow

2. Create an Analysis Directory

Set up a directory for your analysis (referred to as the Analysis Directory):

mkdir $HOME/sarek_project
cd $HOME/sarek_project

• Modify $HOME/sarek_project to better suit your project.

3. Prepare Sample Sheet

Create a sample sheet (samplesheet.csv) with the following format:

subject,sex,tumor,fastq_1,fastq_2
sample1,male,yes,/path/to/sample1_R1.fastq.gz,/path/to/sample1_R2.fastq.gz
sample2,female,no,/path/to/sample2_R1.fastq.gz,/path/to/sample2_R2.fastq.gz

Ensure all paths to the FASTQ files are accurate.

4. Configure ICER Environment

Create an icer.config file for SLURM:

process {
    executor = 'slurm'
}

5. Run nf-core/sarek

Example SLURM Job Submission Script

Below is a shell script for submitting an nf-core/sarek job to SLURM:

#!/bin/bash

#SBATCH --job-name=sarek_job
#SBATCH --time=72:00:00
#SBATCH --mem=64GB
#SBATCH --cpus-per-task=16

cd $HOME/sarek_project
module load Nextflow/23.10.0

nextflow pull nf-core/sarek
nextflow run nf-core/sarek -r 3.14.0 --input ./samplesheet.csv -profile singularity --outdir ./sarek_results --genome GRCh38 -work-dir $SCRATCH/sarek_work -c ./nextflow.config

• Modify --outdir and --genome to match your paths and reference genome.

Note on Reference Genomes

Common reference genomes are located in the research common-data space on the HPCC. Refer to the README file for details. For more guidance on downloading reference genomes from Ensembl, see this GitHub repository.

Execute the pipeline with the following command, including the -w flag for a separate working directory:

nextflow run nf-core/sarek -profile singularity --input samplesheet.csv --genome GRCh38 -c icer.config -w $SCRATCH/sarek_project

• Modify -w $SCRATCH/sarek_project as needed.

6. Monitor and Manage the Run

• Use squeue or sacct to track job status.
• Check the output directory for results.

Best Practices

• Review Logs: Regularly check log files for warnings or errors.
• Optimize Resource Usage: Adjust icer.config to match your dataset requirements.
• Manage Storage: Ensure ample storage for intermediate and final data.

Getting Help

If you encounter issues running nf-core/sarek on the HPCC, consult the following resources:

• nf-core Community: Visit the nf-core website for documentation and support.
• ICER Support: Contact ICER via the MSU ICER support page.
• Slack Channel: Join the nf-core Slack for real-time help.
• Nextflow Documentation: See the Nextflow documentation for additional details.

Conclusion

Running nf-core/sarek on the MSU HPCC is streamlined using Singularity and Nextflow. This guide ensures reproducible and scalable WGS analysis, maximizing the HPCC’s computational resources for bioinformatics research.