Overview

This guide explains how to run the nf-core/cutandrun pipeline for CUT&RUN and CUT&Tag analysis, ensuring reproducibility and efficiency.

Key Benefits of nf-core/cutandrun

nf-core/cutandrun offers:

• Reproducible CUT&RUN/CUT&Tag Analysis: Comprehensive and standardized workflows.
• Portability: Runs seamlessly across various computing infrastructures.
• Scalability: Capable of handling small and large-scale datasets.

Prerequisites

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

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 helps keep outputs and temporary data organized.

Step-by-Step Tutorial

1. Create a Project Directory

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

mkdir $HOME/cutandrun
cd $HOME/cutandrun

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

2. Prepare a Sample Sheet

You need to create a file called samplesheet.csv that lists your samples and their FASTQ file paths. Use a text editor (like nano) to create this file:

nano samplesheet.csv

Then, add your sample information in CSV format. For example:

sample,fastq_1,fastq_2,replicate,antibody
sample1,/path/to/sample1_R1.fastq.gz,/path/to/sample1_R2.fastq.gz,1,H3K27me3
sample2,/path/to/sample2_R1.fastq.gz,/path/to/sample2_R2.fastq.gz,1,IgG

Save the file (in nano, press Ctrl+O then Ctrl+X to exit).

3. Create a Configuration File

Do not type file content directly into the terminal. Use a text editor instead. Create a file named icer.config:

nano icer.config

Paste the following content into the file:

process {
    executor = 'slurm'
}

Save and exit the editor.

4. Prepare the Job Submission Script

Now, create a shell script to run the pipeline. Create a file called run_cutandrun.sh:

nano run_cutandrun.sh

Paste in the following script:

#!/bin/bash --login
#SBATCH --job-name=cutandrun
#SBATCH --time=24:00:00
#SBATCH --mem=4GB
#SBATCH --cpus-per-task=1
#SBATCH --output=cutandrun-%j.out

# Load Nextflow
module purge
module load Nextflow

# Set the paths to the genome files
GENOME_DIR="/mnt/research/common-data/Bio/genomes/Ensembl_GRCm39_mm39" #Example GRCm39
FASTA="$GENOME_DIR/genome.fa" # Example FASTA
GTF="$GENOME_DIR/genes.gtf" # Example GTF

# Define the samplesheet, outdir, workdir, and config
SAMPLESHEET="$HOME/cutandrun/samplesheet.csv" # Example path to sample sheet
OUTDIR="$HOME/cutandrun/results" # Example path to results directory
WORKDIR="$SCRATCH/cutandrun/work" # Example path to work directory
CONFIG="$HOME/cutandrun/icer.config" # Example path to icer.config file

# Run the CUT&RUN analysis
nextflow pull nf-core/cutandrun
nextflow run nf-core/cutandrun -r 3.2.2 -profile singularity -work-dir $WORKDIR -resume \
--input $SAMPLESHEET \
--outdir $OUTDIR \
--fasta $FASTA \
--gtf $GTF \
-c $CONFIG

5. Submit Your Job

Submit your job to SLURM by typing:

sbatch run_cutandrun.sh

This sends your job to the scheduler on the HPCC.

6. Monitor Your Job

Check the status of your job with:

squeue -u $USER

After completion, your output files will be in the results folder inside your cutandrun directory.

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.

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 sufficient storage for intermediate and final results.

Getting Help

If you encounter issues running nf-core/cutandrun on the HPCC, consider these 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 assistance.
• Nextflow Documentation: See the Nextflow documentation for further details.

Conclusion

Running nf-core/cutandrun on the MSU HPCC is simplified using Singularity and Nextflow. This guide ensures reproducible and efficient CUT\&RUN and CUT\&Tag analysis, leveraging the HPCC’s computational capabilities for bioinformatics research.