CUT&RUN and CUT&Tag Articles and Analysis Methods

This is a repo that contains relevant info regarding CUT&RUN and CUT&Tag computational analysis and interpretation, including protocols, pipelines, peak calling algorithms, benchmarking articles, and applications of these techniques.

CUT&RUN Articles

CUT&RUN was first described in this article by Pete Skene and Steve Henikoff, published in eLife in 2017:

Peter J Skene & Steven Henikoff. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. eLife (2017). https://doi.org/10.7554/eLife.21856

This was followed by a detailed protocol for CUT&RUN by Peter Skene et al. in Nature Protocols in 2018:

Peter J Skene, Jorja G Henikoff, & Steven Henikoff. Targeted in situ genome-wide profiling with high efficiency for low cell numbers. Nature Protocols (2018). https://doi.org/10.1038/nprot.2018.015

autoCUT&RUN was next described by Derek Janssens et al. in Epigenetics & Chromatin in 2018:

Next came an improvement on the original protocol that expanded antibody compatibility by using pAG-MNase instead of pA-MNase, a salt ion modification to the digestion step, and normalization using the E. coli DNA that is carried over from purification of the MNase enzyme. This was described by Michael Meers et al. in eLife in 2019:

Michael P Meers, Terri D Bryson, Jorja G Henikoff, & Steven Henikoff. Improved CUT&RUN chromatin profiling tools. eLife (2019). https://doi.org/10.7554/eLife.46314

CUT&Tag Articles

CUT&Tag was first described by Hatice Kaya-Okur in Nature Communications in 2019:

Hatice S. Kaya-Okur, Steven J. Wu, Christine A. Codomo, et al. CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat Comm (2019). https://doi.org/10.1038/s41467-019-09982-5

A detailed protocol for CUT&Tag was published by Hatice Kaya-Okur in Nature Protocols in 2020:

Hatice S. Kaya-Okur, Derek H. Janssens, Jorja G. Henikoff, Kami Ahmad, & Steven Henikoff. Efficient low-cost chromatin profiling with CUT&Tag. Nature Protocols (2020). https://doi.org/10.1038/s41596-020-0373-x

autoCUT&Tag article:

Derek H. Janssens, et al. Automated CUT&Tag profiling of chromatin heterogeneity in mixed-lineage leukemia. Nature Genetics (2021). https://doi.org/10.1038/s41588-021-00941-9

CUT&TAG2for1 article:

Derek H. Janssens, Dominik J. Otto, et al. CUT&Tag2for1: a modified method for simultaneous profiling of the accessible and silenced regulome in single cells. Genome Biology (2022). https://doi.org/10.1186/s13059-022-02642-w

Mechanism of BAF nucleosome eviction with RNAPII (this paper uses CUT&Tag, CUTAC, CUT&RUN, & CUT&RUN.ChIP):

Sandipan Brahma & Steven Henikoff. The BAF chromatin remodeler synergizes with RNA polymerase II and transcription factors to evict nucleosomes. Nature Genetics (2023). https://doi.org/10.1038/s41588-023-01603-8

Single-cell CUT&Tag articles:

Marek Bartosovic, Mukund Kabbe, & Gonçalo Castelo-Branco. Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nature Biotechnology (2021). https://doi.org/10.1038/s41587-021-00869-9

Steven J. Wu, Scott N. Furlan, et al. Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression. Nature Biotechnology (2021). https://doi.org/10.1038/s41587-021-00865-z

Chenxu Zhu, et al., Bing Ren. Joint profiling of histone modifications and transcriptome in single cells from mouse brain. Nature Methods (2021). https://doi.org/10.1038/s41592-021-01060-3

Michael P. Meers, et al., Steven Henikoff. Multifactorial profiling of epigenetic landscapes at single-cell resolution using MulTI-Tag. Nature Biotechnology (2022). https://doi.org/10.1038/s41587-022-01522-9

Derek H. Janssens, Jacob E. Greene, et al., Steven Henikoff. Scalable single-cell profiling of chromatin modifications with sciCUT&Tag. Nature Protocols (2023). https://doi.org/10.1038/s41596-023-00905-9

CUTAC Articles

Original CUTAC paper:

Steven Henikoff, Jorja G Henikoff, Hatice S Kaya-Okur, & Kami Ahmad. Efficient chromatin accessibility mapping in situ by nucleosome-tethered tagmentation. eLife (2020). https://doi.org/10.7554/eLife.63274

CUTAC Bio-protocol article:

Steven Henikoff, Jorja G Henikoff, & Kami Ahmad. Simplified Epigenome Profiling Using Antibody-tethered Tagmentation. Bio-protocol (2021). https://doi.org/10.21769/BioProtoc.4043

FFPE-CUTAC paper:

Steven Henikoff, et al. Epigenomic analysis of formalin-fixed paraffin-embedded samples by CUT&Tag. Nature Communications (2023). https://doi.org/10.1038/s41467-023-41666-z

RNA Pol II activity, hypertranscription, and biomarkers of human tumors using FFPE-CUTAC paper:

Steven Henikoff, Ye Zheng, et al. RNA polymerase II at histone genes predicts outcome in human cancer. Science (2025). https://doi.org/10.1126/science.ads2169

Peak Calling and Benchmarking Articles

SEACR:

Michael P. Meers, Dan Tenenbaum, & Steven Henikoff. Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling. Epigenetics & Chromatin (2019). https://doi.org/10.1186/s13072-019-0287-4

MACS, MACS2, and MACS3

The seminal MACS peak calling paper came out of Shirley Liu's lab in 2008 (cited over 16k times):

Yong Zhang, et al. Model-based Analysis of ChIP-Seq (MACS). Genome Biology (2008). https://doi.org/10.1186/gb-2008-9-9-r137

Additional MACS/MACS2/MACS3 papers and repos:

Jianxing Feng, Tao Liu, Yong Zhang. Using MACS to Identify Peaks from ChIP-Seq Data. Current Protocols in Bioinformatics (2011). https://doi.org/10.1002/0471250953.bi0214s34

Jianxing Feng, Tao Liu, et al. Identifying ChIP-seq enrichment using MACS. Nature Protocols (2012). https://doi.org/10.1038/nprot.2012.101

Su Wang, et al. Target analysis by integration of transcriptome and ChIP-seq data with BETA. Nature Protocols (2013). https://doi.org/10.1038/nprot.2013.150

John M. Gaspar. Improved peak-calling with MACS2. bioRxiv (2018). https://doi.org/10.1101/496521

GoPeaks:

William M. Yashar, et al. GoPeaks: histone modification peak calling for CUT&Tag. Genome Biology (2022). https://doi.org/10.1186/s13059-022-02707-w

Comparison of CUT&Tag peaks with ENCODE ChIP-seq peaks for K562 cells:

Leyla Abbasova, Paulina Urbanaviciute, Di Hu, Joy N. Ismail, Brian M. Schilder, Alexi Nott, Nathan G. Skene, & Sarah J. Marzi. CUT&Tag recovers up to half of ENCODE ChIP-seq histone acetylation peaks. Nature Communications (2025). https://doi.org/10.1038/s41467-025-58137-2

Benchmarking peak calling methods for CUT&RUN:

Amin Nooranikhojasteh, Ghazaleh Tavallaee, & Elias Orouji. Benchmarking peak calling methods for CUT&RUN. Bioinformatics (2025). https://doi.org/10.1093/bioinformatics/btaf375

Article benchmarking scCUT&Tag analysis pipelines:

Félix Raimundo, Pacôme Prompsy, Jean-Philippe Vert, & Céline Vallot. A benchmark of computational pipelines for single-cell histone modification data. Genome Biology (2023). https://doi.org/10.1186/s13059-023-02981-2

Wet-lab Protocols

Computational Analysis

CUT&Tag data analysis tutorial

https://dx.doi.org/10.17504/protocols.io.bjk2kkye

CUT&Tag data analysis for a time series

https://www.protocols.io/view/cut-amp-tag-data-processing-and-analysis-tutorial-5jyl8py98g2w/v2

Fred Hutch Choosing Genomic Tools Book

Chapter 19: CUT&RUN and CUT&Tag (Written by Ye Zheng)

https://hutchdatascience.org/Choosing_Genomics_Tools/cutrun-and-cuttag.html

Fred Hutch SEACR Peak Calling GitHub Repo:

https://github.com/FredHutch/SEACR

MACS3 Peak Calling Website:

https://macs3-project.github.io/MACS/

Useful paper for Tn5 chemistry behind CUT&Tag:

Simone Picelli et al. Tn5 transposase and tagmentation procedures for massively scaled sequencing projects. Genome Research (2014). https://doi.org/10.1101/gr.177881.114

Other computational tools for CUT&RUN, CUT&Tag, and CUTAC:

Note: This is not meant to be an exhaustive list. However, it should include the most relavent articles and the common/effective tools used for analyzing and visualizing CUT&RUN and CUT&Tag data. If there are any glaring ommisions, please feel free to post an issue on this repo.

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README.md		README.md
cutrun_normalization.md		cutrun_normalization.md
nf-core_cutandrun_notes.md		nf-core_cutandrun_notes.md
normalization.md		normalization.md

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