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

被引:0
|
作者
Jeffrey M. Granja
M. Ryan Corces
Sarah E. Pierce
S. Tansu Bagdatli
Hani Choudhry
Howard Y. Chang
William J. Greenleaf
机构
[1] Stanford University School of Medicine,Department of Genetics
[2] Stanford University,Program in Biophysics
[3] Stanford University,Center for Personal Dynamic Regulomes
[4] Stanford University School of Medicine,Department of Pathology
[5] Gladstone Institute of Data Science and Biotechnology,Gladstone Institute of Neurological Disease
[6] University of California San Francisco,Department of Neurology
[7] Stanford University School of Medicine,Program in Cancer Biology
[8] King Abdulaziz University,Department of Biochemistry, Faculty of Science, Cancer and Mutagenesis Unit, King Fahd Center for Medical Research
[9] Stanford University,Howard Hughes Medical Institute
[10] Stanford University,Department of Applied Physics
[11] Chan Zuckerberg Biohub,undefined
来源
Nature Genetics | 2021年 / 53卷
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摘要
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.
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页码:403 / 411
页数:8
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