{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T12:37:43Z","timestamp":1784810263124,"version":"3.55.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T00:00:00Z","timestamp":1625788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["R01HG009663"],"award-info":[{"award-number":["R01HG009663"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"New York Stem Cell Foundation and NIH","award":["R01DK103794"],"award-info":[{"award-number":["R01DK103794"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Genome-wide profiling of transcription factor binding and chromatin states is a widely-used approach for mechanistic understanding of gene regulation. Recent technology development has enabled such profiling at single-cell resolution. However, an end-to-end computational pipeline for analyzing such data is still lacking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we have developed a flexible pipeline for analysis and visualization of single-cell CUT&amp;Tag and CUT&amp;RUN data, which provides functions for sequence alignment, quality control, dimensionality reduction, cell clustering, data aggregation and visualization. Furthermore, it is also seamlessly integrated with the functions in original CUT&amp;RUNTools for population-level analyses. As such, this provides a valuable toolbox for the community.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>https:\/\/github.com\/fl-yu\/CUT-RUNTools-2.0.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab507","type":"journal-article","created":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T23:14:55Z","timestamp":1625699695000},"page":"252-254","source":"Crossref","is-referenced-by-count":68,"title":["CUT&amp;RUNTools 2.0: a pipeline for single-cell and bulk-level CUT&amp;RUN and CUT&amp;Tag data analysis"],"prefix":"10.1093","volume":"38","author":[{"given":"Fulong","family":"Yu","sequence":"first","affiliation":[{"name":"Department of Pediatric Oncology, Dana-Farber Cancer Institute , Boston, MA 02215, USA"},{"name":"Division of Hematology\/Oncology, Boston Children\u2019s Hospital , Boston, MA 02115, USA"},{"name":"Department of Pediatrics, Harvard Medical School , Boston, MA 02115, USA"},{"name":"Program in Medical & Population Genetics, Broad Institute of MIT and Harvard , Cambridge, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0044-443X","authenticated-orcid":false,"given":"Vijay G","family":"Sankaran","sequence":"additional","affiliation":[{"name":"Department of Pediatric Oncology, Dana-Farber Cancer Institute , Boston, MA 02215, USA"},{"name":"Division of Hematology\/Oncology, Boston Children\u2019s Hospital , Boston, MA 02115, USA"},{"name":"Department of Pediatrics, Harvard Medical School , Boston, MA 02115, USA"},{"name":"Program in Medical & Population Genetics, Broad Institute of MIT and Harvard , Cambridge, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2283-4714","authenticated-orcid":false,"given":"Guo-Cheng","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Pediatric Oncology, Dana-Farber Cancer Institute , Boston, MA 02215, USA"},{"name":"Division of Hematology\/Oncology, Boston Children\u2019s Hospital , Boston, MA 02115, USA"},{"name":"Department of Pediatrics, Harvard Medical School , Boston, MA 02115, USA"},{"name":"Department of Genetics and Genomic Sciences, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai , New York, NY 10029, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,7,9]]},"reference":[{"key":"2023020108385639000_btab507-B1","doi-asserted-by":"crossref","first-page":"1164","DOI":"10.1038\/s41556-019-0383-5","article-title":"Profiling chromatin states using single-cell itChIP-seq","volume":"21","author":"Ai","year":"2019","journal-title":"Nat. Cell Biol"},{"key":"2023020108385639000_btab507-B2","doi-asserted-by":"crossref","first-page":"e10","DOI":"10.1093\/nar\/gky950","article-title":"Classifying cells with Scasat, a single-cell ATAC-seq analysis tool","volume":"47","author":"Baker","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023020108385639000_btab507-B3","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1038\/leu.2012.280","article-title":"Role of early B-cell factor 1 (EBF1) in Hodgkin lymphoma","volume":"27","author":"Bohle","year":"2013","journal-title":"Leukemia"},{"key":"2023020108385639000_btab507-B4","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1038\/s41592-019-0367-1","article-title":"cisTopic: cis-regulatory topic modeling on single-cell ATAC-seq data","volume":"16","author":"Bravo Gonzalez-Blas","year":"2019","journal-title":"Nat. Methods"},{"key":"2023020108385639000_btab507-B5","doi-asserted-by":"crossref","first-page":"3747","DOI":"10.1038\/s41467-019-11559-1","article-title":"Mapping histone modifications in low cell number and single cells using antibody-guided chromatin tagmentation (ACT-seq)","volume":"10","author":"Carter","year":"2019","journal-title":"Nat. Commun"},{"key":"2023020108385639000_btab507-B6","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1186\/s13059-019-1854-5","article-title":"Assessment of computational methods for the analysis of single-cell ATAC-seq data","volume":"20","author":"Chen","year":"2019","journal-title":"Genome Biol"},{"key":"2023020108385639000_btab507-B7","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1126\/science.aab1601","article-title":"Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing","volume":"348","author":"Cusanovich","year":"2015","journal-title":"Science"},{"key":"2023020108385639000_btab507-B8","doi-asserted-by":"crossref","first-page":"16484","DOI":"10.1073\/pnas.1417215111","article-title":"EGR2 is critical for peripheral naive T-cell differentiation and the T-cell response to influenza","volume":"111","author":"Du","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023020108385639000_btab507-B9","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1038\/s41467-021-21583-9","article-title":"Comprehensive analysis of single cell ATAC-seq data with SnapATAC","volume":"12","author":"Fang","year":"2021","journal-title":"Nat. Commun"},{"key":"2023020108385639000_btab507-B10","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1038\/s41588-021-00790-6","article-title":"ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis","volume":"53","author":"Granja","year":"2021","journal-title":"Nat. Genet"},{"key":"2023020108385639000_btab507-B11","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.1016\/j.cell.2019.03.014","article-title":"Profiling of pluripotency factors in single cells and early embryos","volume":"177","author":"Hainer","year":"2019","journal-title":"Cell"},{"key":"2023020108385639000_btab507-B12","doi-asserted-by":"crossref","first-page":"2930","DOI":"10.1093\/bioinformatics\/btx315","article-title":"Single-cell regulome data analysis by SCRAT","volume":"33","author":"Ji","year":"2017","journal-title":"Bioinformatics"},{"key":"2023020108385639000_btab507-B13","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1186\/s13059-020-02075-3","article-title":"Single-cell ATAC-seq signal extraction and enhancement with SCATE","volume":"21","author":"Ji","year":"2020","journal-title":"Genome Biol"},{"key":"2023020108385639000_btab507-B14","doi-asserted-by":"crossref","first-page":"1930","DOI":"10.1038\/s41467-019-09982-5","article-title":"CUT&Tag for efficient epigenomic profiling of small samples and single cells","volume":"10","author":"Kaya-Okur","year":"2019","journal-title":"Nat. Commun"},{"key":"2023020108385639000_btab507-B15","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1038\/sj.leu.2403466","article-title":"Distinct gene signatures of transient and acute megakaryoblastic leukemia in Down syndrome","volume":"18","author":"Lightfoot","year":"2004","journal-title":"Leukemia"},{"key":"2023020108385639000_btab507-B16","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1016\/j.molcel.2018.06.044","article-title":"Cicero predicts cis-regulatory DNA interactions from single-cell chromatin accessibility data","volume":"71","author":"Pliner","year":"2018","journal-title":"Mol. Cell"},{"key":"2023020108385639000_btab507-B17","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1038\/nmeth.4401","article-title":"chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data","volume":"14","author":"Schep","year":"2017","journal-title":"Nat. Methods"},{"key":"2023020108385639000_btab507-B18","article-title":"An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites","volume":"6, e21856","author":"Skene","year":"2017","journal-title":"Elife"},{"key":"2023020108385639000_btab507-B19","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1038\/nprot.2018.015","article-title":"Targeted in situ genome-wide profiling with high efficiency for low cell numbers","volume":"13","author":"Skene","year":"2018","journal-title":"Nat. Protoc"},{"key":"2023020108385639000_btab507-B20","doi-asserted-by":"crossref","first-page":"3818","DOI":"10.1093\/bioinformatics\/btz141","article-title":"Destin: toolkit for single-cell analysis of chromatin accessibility","volume":"35","author":"Urrutia","year":"2019","journal-title":"Bioinformatics"},{"key":"2023020108385639000_btab507-B21","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1038\/341405a0","article-title":"Segmental expression of Hox-2 homoeobox-containing genes in the developing mouse hindbrain","volume":"341","author":"Wilkinson","year":"1989","journal-title":"Nature"},{"key":"2023020108385639000_btab507-B22","doi-asserted-by":"crossref","first-page":"4576","DOI":"10.1038\/s41467-019-12630-7","article-title":"SCALE method for single-cell ATAC-seq analysis via latent feature extraction","volume":"10","author":"Xiong","year":"2019","journal-title":"Nat. Commun"},{"key":"2023020108385639000_btab507-B23","doi-asserted-by":"crossref","first-page":"2410","DOI":"10.1038\/s41467-018-04629-3","article-title":"Unsupervised clustering and epigenetic classification of single cells","volume":"9","author":"Zamanighomi","year":"2018","journal-title":"Nat. Commun"},{"key":"2023020108385639000_btab507-B24","doi-asserted-by":"crossref","first-page":"R137","DOI":"10.1186\/gb-2008-9-9-r137","article-title":"Model-based analysis of ChIP-Seq (MACS)","volume":"9","author":"Zhang","year":"2008","journal-title":"Genome Biol"},{"key":"2023020108385639000_btab507-B25","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1186\/s13059-019-1802-4","article-title":"CUT&RUNTools: a flexible pipeline for CUT&RUN processing and footprint analysis","volume":"20","author":"Zhu","year":"2019","journal-title":"Genome Biol"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btab507\/39277593\/btab507.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/1\/252\/49006448\/btab507.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/1\/252\/49006448\/btab507.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T14:54:29Z","timestamp":1675263269000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/1\/252\/6318389"}},"subtitle":[],"editor":[{"given":"Tobias","family":"Marschall","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2021,7,9]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12,22]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btab507","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.01.26.428013","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,1,1]]},"published":{"date-parts":[[2021,7,9]]}}}