CUT&RUN ONT workflow

Workflow to do the following:

1. Trims adapters
2. Filters reads between 100 - 10kbp
3. Aligns with bwa-mem
4. Normalizes to sample_baseline and generate bigWig for visualization.

Normalized CENP-A enrichment in HGSVC NA20355_chr8_haplotype1-0000017

Getting Started

Clone the repo.

git clone https://github.com/logsdon-lab/Snakemake-CutNRun.git
cd Snakemake-CutNRun

Create conda environment with Snakemake.

conda create --name smk snakemake==9.5.0

Configuation

Modify to fit your use-case.

• Expects a baseline to compare treatment enrichment against.
• Only one sample possible.

ref: data/asm/asm.fa
sample_baseline: IgG
samples:
  CENP-A:
    path: data/CENP-A/reads.bam
  IgG:
    path: data/IgG/reads.bam

Run

To run the workflow and install necessary dependencies with conda.

snakemake -np --configfile config.yaml -c 12 --sdm conda

Output

Normalized bigWig file under results/(!sample_baseline)/reads_to_ref.bam.

• ex. results/CENP-A/reads_to_ref.bam
• This can be loaded in IGV with the aligned reference.

Test

Run test case of CENP-A enrichment in HGSVC NA20355_chr8_haplotype1-0000017.

# Note: Reads subset for testing purposes.
# See docs/IGV_NA20355_chr8_haplotype1-0000017_no_subset.png
snakemake -p --configfile test/config.yaml -c 12 --sdm conda

Cite

Gao S, Oshima KK, Chuang SC, Loftus M, Montanari A, Gordon DS, Human Genome Structural Variation Consortium, Human Pangenome Reference Consortium, Hsieh P, Konkel MK, Ventura M, Logsdon GA. A global view of human centromere variation and evolution. bioRxiv. 2025. p. 2025.12.09.693231. doi:10.64898/2025.12.09.693231