The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling
Open accessAbstract
BACKGROUND: CUT&RUN is an efficient epigenome profiling method that identifies sites of DNA binding protein enrichment genome-wide with high signal to noise and low sequencing requirements. Currently, the analysis of CUT&RUN data is complicated by its exceptionally low background, which renders programs designed for analysis of ChIP-seq data vulnerable to oversensitivity in identifying sites of protein binding. RESULTS: Here we introduce Sparse Enrichment Analysis for CUT&RUN (SEACR), an analysis strategy that uses the global distribution of background signal to calibrate a simple threshold for peak calling. SEACR discriminates between true and false-positive peaks with near-perfect specificity from "gold standard" CUT&RUN datasets and efficiently identifies enriched regions for several different protein targets. We also introduce a web server ( http://seacr.fredhutch.org ) for plug-and-play analysis with SEACR that facilitates maximum accessibility across users of all skill levels. CONCLUSIONS: SEACR is a highly selective peak caller that definitively validates the accuracy of CUT&RUN for datasets with known true negatives. Its ease of use and performance in comparison with existing peak calling strategies make it an ideal choice for analyzing CUT&RUN data.
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“peaks were called using SEACR (94) with a peak threshold of 0.05 using spike in normalization performed using the Escherichia coli genome K12.”
From Synergy between regulatory elements can render cohesin dispensable for distal enhancer function (2026) · cites this paper as [94]
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Cites
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845
Genome-Wide Mapping of in Vivo Protein-DNA Interactions
Johnson, D. S., Mortazavi, A., Myers, R. M., & Wold, B. (2007) · Science · doi:10.1126/science.1141319 · Cited by 2,927
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Kaya-Okur, H. S., Wu, S. J., Codomo, C. A., Pledger, E. S., Bryson, T. D., Henikoff, J. G., Ahmad, K., & Henikoff, S. (2019) · Nature Communications · doi:10.1038/s41467-019-09982-5 · Cited by 2,187
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Skene, P. J., & Henikoff, S. (2017) · eLife · doi:10.7554/elife.21856 · Cited by 1,737
Self-citationRobertson, G., Hirst, M., Bainbridge, M., Bilenky, M., Zhao, Y., Zeng, T., Euskirchen, G., Bernier, B., Varhol, R., Delaney, A., et al. (2007) · Nature Methods · doi:10.1038/nmeth1068 · Cited by 1,454
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Skene, P. J., Henikoff, J. G., & Henikoff, S. (2018) · Nature Protocols · doi:10.1038/nprot.2018.015 · Cited by 803
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Romero, M. A., Chien, P., Nicoletti, C., Liliom, H. L., Cox, G., Skuratovsky, E., Saleh, K. K., Gibbs, D., Gane, L., Hoang, D.-H., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.23.701436
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Singh, N., Batz, Z. A., Advani, J., English, M. A., Maddala, R., Rao, P. V., & Swaroop, A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.12.711121
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Hartge, M. K., Hernández, N. P., Pavlik, T., Polakova, N., Schönauer, E., Huber, J., Striedner, Y., Mair, T., Tiemann‐Boege, I., Weissensteiner, M. H., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.31.742039
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Rizk, J. G., Ghaibour, K. C., Souali‐Crespo, S., Calvano, E., Bilger, A., Jacobs, H., Messaddeq, N., Cai, Q., Grandgirard, E., Sahu, R., et al. (2026) · Science Advances · doi:10.1126/sciadv.aec8073
Qian, Q., Xu, Y., & Wei, L. (2026) · Acta Biochimica et Biophysica Sinica · doi:10.3724/abbs.2026165
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Huang, X., Peng, Y., Hu, X., Wang, Y., Zhang, Z., Huang, X., Luo, X., Zhang, S., Zhao, Z., Farmer, E. E., et al. (2026) · Cell · doi:10.1016/j.cell.2026.08.038
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Wang, Y., Shi, H., Chapman, N. M., Anil, K. C., Sun, R., Song, H., Meng, X., Sun, X., & Chi, H. (2026) · Nature · doi:10.1038/s41586-026-11059-5
Manzini, V., Nisio, E. D., Piana, A., Perticaroli, V., Asteriti, I. A., Polverino, F., Negri, R., & Licursi, V. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27198774
Kita, K., Masayasu, S. E. G. A., Uchida, Y., Chiba, T., Matsushima, T., & Asahara, H. (2026) · STAR Protocols · doi:10.1016/j.xpro.2026.104889
Eghbali, A., Säflund, M., Askari, M., Abdi, M. M., Farrants, A. Ö., Yu, T., & Özata, D. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.07.757370
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黄伟伟, Yu, C., Wang, Y., Sun, N., Wang, L., Ren, J., Xu, Y., Guo, X., Li, X., Mao, Y., et al. (2026) · Nature Metabolism · doi:10.1038/s42255-026-01625-6
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Metadata
- Authors
- Meers, M. P., Tenenbaum, D., & Henikoff, S.
- Affiliations
- Fred Hutch Cancer Center (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Henikoff, Steven
- Venue
- Epigenetics & Chromatin
- Published
- 2019-07-12
- Volume
- 12
- Issue
- 1
- Pages
- 42-42
- ISSN
- 1756-8935 (ISSN-L)
- PMC
- PMC6624997
- OpenAlex
- W2958184371
- Cited by
- 556
- References
- 21
- Citations by year
- 2026: 86 · 2025: 123 · 2024: 126 · 2023: 95 · 2022: 65 · 2021: 44 · 2020: 16
- FWCI
- 10.34
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Epigenetics & Chromatin (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Howard Hughes Medical Institute (Henikoff)
- National Human Genome Research Institute (1R01HG010492)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- peak calling, CUT&RUN, chromatin profiling, protein-DNA binding sites, epigenetic profiling, web server
- MeSH terms
- Algorithms, Animals, Binding Sites, Chromatin, DNA-Binding Proteins, Humans, Protein Binding, Genome, Sequence Analysis, DNA, Epigenesis, Genetic, Chromatin Immunoprecipitation, Epigenomics
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