ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis

The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulato...

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Published in:	Nature genetics Vol. 53; no. 3; pp. 403 - 411
Main Authors:	Granja, Jeffrey M., Corces, M. Ryan, Pierce, Sarah E., Bagdatli, S. Tansu, Choudhry, Hani, Chang, Howard Y., Greenleaf, William J.
Format:	Journal Article
Language:	English
Published:	New York Nature Publishing Group US 01.03.2021 Nature Publishing Group
Subjects:	38/22 38/23 38/39 45 631/208/176 631/208/177 631/208/200 Accessibility Agriculture Animal Genetics and Genomics Animals Biomedical and Life Sciences Biomedicine Cancer Research Chromatin Chromatin - genetics Chromatin - metabolism Cluster Analysis Clustering Computer programs Datasets Deoxyribonucleic acid DNA Electronic data processing Footprinting Gene expression Gene Expression Regulation Gene Function Gene regulation Gene sequencing Genetic regulation Genetic research Genome Genomics Human Genetics Humans Identification Mice Science Sequence Analysis, RNA - methods Single-Cell Analysis - methods Software Software packages technical-report Technology application Transcription factors Transcription Factors - genetics Transcription Factors - metabolism UNIX User-Computer Interface Web Browser United States
ISSN:	1061-4036, 1546-1718, 1546-1718
Online Access:	Get full text
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Abstract	The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/ ) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells. ArchR is a software suite that enables efficient and end-to-end analysis of single-cell chromatin accessibility data (scATAC-seq).
AbstractList	The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/ ) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells.The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/ ) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells. The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells. The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; ArchR is a software suite that enables efficient and end-to-end analysis of single-cell chromatin accessibility data (scATAC-seq). The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/ ) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells. The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://vww.archrproject.com/) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells. The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells. ArchR is a software suite that enables efficient and end-to-end analysis of single-cell chromatin accessibility data (scATAC-seq). The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/ ) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells. ArchR is a software suite that enables efficient and end-to-end analysis of single-cell chromatin accessibility data (scATAC-seq).
Audience	Academic
Author	Bagdatli, S. Tansu Greenleaf, William J. Granja, Jeffrey M. Chang, Howard Y. Corces, M. Ryan Choudhry, Hani Pierce, Sarah E.
Author_xml	– sequence: 1 givenname: Jeffrey M. orcidid: 0000-0001-8402-3442 surname: Granja fullname: Granja, Jeffrey M. email: jgranja.stanford@gmail.com organization: Department of Genetics, Stanford University School of Medicine, Program in Biophysics, Stanford University, Center for Personal Dynamic Regulomes, Stanford University – sequence: 2 givenname: M. Ryan surname: Corces fullname: Corces, M. Ryan organization: Center for Personal Dynamic Regulomes, Stanford University, Department of Pathology, Stanford University School of Medicine, Gladstone Institute of Neurological Disease, Gladstone Institute of Data Science and Biotechnology, Department of Neurology, University of California San Francisco – sequence: 3 givenname: Sarah E. surname: Pierce fullname: Pierce, Sarah E. organization: Department of Genetics, Stanford University School of Medicine, Program in Cancer Biology, Stanford University School of Medicine – sequence: 4 givenname: S. Tansu surname: Bagdatli fullname: Bagdatli, S. Tansu organization: Department of Genetics, Stanford University School of Medicine – sequence: 5 givenname: Hani surname: Choudhry fullname: Choudhry, Hani organization: Department of Biochemistry, Faculty of Science, Cancer and Mutagenesis Unit, King Fahd Center for Medical Research, King Abdulaziz University – sequence: 6 givenname: Howard Y. orcidid: 0000-0002-9459-4393 surname: Chang fullname: Chang, Howard Y. email: howchang@stanford.edu organization: Department of Genetics, Stanford University School of Medicine, Center for Personal Dynamic Regulomes, Stanford University, Howard Hughes Medical Institute, Stanford University – sequence: 7 givenname: William J. orcidid: 0000-0003-1409-3095 surname: Greenleaf fullname: Greenleaf, William J. email: wjg@stanford.edu organization: Department of Genetics, Stanford University School of Medicine, Center for Personal Dynamic Regulomes, Stanford University, Department of Applied Physics, Stanford University, Chan Zuckerberg Biohub
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/33633365$$D View this record in MEDLINE/PubMed
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Snippet	The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of...
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SubjectTerms	38/22 38/23 38/39 45 631/208/176 631/208/177 631/208/200 Accessibility Agriculture Animal Genetics and Genomics Animals Biomedical and Life Sciences Biomedicine Cancer Research Chromatin Chromatin - genetics Chromatin - metabolism Cluster Analysis Clustering Computer programs Datasets Deoxyribonucleic acid DNA Electronic data processing Footprinting Gene expression Gene Expression Regulation Gene Function Gene regulation Gene sequencing Genetic regulation Genetic research Genome Genomics Human Genetics Humans Identification Mice Science Sequence Analysis, RNA - methods Single-Cell Analysis - methods Software Software packages technical-report Technology application Transcription factors Transcription Factors - genetics Transcription Factors - metabolism UNIX User-Computer Interface Web Browser
Title	ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis
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