ArticleBioinformatics (Oxford, England)2025
Benchmarking peak calling methods for CUT&RUN.
Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Integrative Epigenomics: Bioinformatics Strategies for Multi-Omics Data Analysis in Health and Disease.Epigenomes · 2026Review
- Dosage compensation defects due to roX RNA loss are rescued by recalibration of X/autosome stoichiometry.Nucleic acids research · 2026Article
- Many roads lead to a plant cistrome: mapping and interpreting transcription factor binding in plants.Genome biology · 2026Review
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Authors and funding
3 authors.
Funding
Abstract
motivationCleavage Under Targets and Release Using Nuclease (CUT&RUN) has rapidly gained prominence as an effective approach for mapping protein-DNA interactions, especially histone modifications, offering substantial improvements over conventional chromatin immunoprecipitation sequencing (ChIP-seq). However, the effectiveness of this technique is contingent upon accurate peak identification, necessitating the use of optimal peak calling methods tailored to the unique characteristics of CUT&RUN data.
resultsHere, we benchmark four prominent peak calling tools, MACS2, SEACR, GoPeaks, and LanceOtron, evaluating their performance in identifying peaks from CUT&RUN datasets. Our analysis utilizes in-house data of three histone marks (H3K4me3, H3K27ac, and H3K27me3) from mouse brain tissue, as well as samples from the 4D Nucleome database. We systematically assess these tools based on parameters such as the number of peaks called, peak length distribution, signal enrichment, and reproducibility across biological replicates. Our findings reveal substantial variability in peak calling efficacy, with each method demonstrating distinct strengths in sensitivity, precision, and applicability depending on the histone mark in question. These insights provide a comprehensive evaluation that will assist in selecting the most suitable peak caller for high-confidence identification of regions of interest in CUT&RUN experiments, ultimately enhancing the study of chromatin dynamics and transcriptional regulation. AVAILABILITY AND IMPLEMENTATION: The CUT&RUN data generated in this study have been deposited in the Gene Expression Omnibus (GEO) under the accession number GSE282809. All the 4D Nucleome datasets can be obtained from the 4D Nucleome Data Portal (https://data.4dnucleome.org/). All scripts used for data processing, figure generation, and analysis are available in the following GitHub repository: https://github.com/OroujiLab/CUTandRun_Peak_Calling/, and have also been archived on Zenodo.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.