Comprehensive analysis of single cell ATAC-seq data with SnapATAC

Rongxin Fang, Sebastian Preissl, Yang Li, Xiaomeng Hou, Jacinta Lucero, Xinxin Wang, Amir Motamedi, Andrew K. Shiau, Xinzhu Zhou, Fangming Xie, Eran A. Mukamel, Kai Zhang, Yanxiao Zhang, M. Margarita Behrens, Joseph R. Ecker and Bing Ren ()
Additional contact information
Rongxin Fang: Ludwig Institute for Cancer Research
Sebastian Preissl: University of California, San Diego
Yang Li: Ludwig Institute for Cancer Research
Xiaomeng Hou: University of California, San Diego
Jacinta Lucero: The Salk Institute for Biological Studies
Xinxin Wang: University of California, San Diego
Amir Motamedi: Ludwig Institute for Cancer Research
Andrew K. Shiau: Ludwig Institute for Cancer Research
Xinzhu Zhou: University of California San Diego
Fangming Xie: University of California, San Diego
Eran A. Mukamel: University of California, San Diego
Kai Zhang: Ludwig Institute for Cancer Research
Yanxiao Zhang: Ludwig Institute for Cancer Research
M. Margarita Behrens: The Salk Institute for Biological Studies
Joseph R. Ecker: The Salk Institute for Biological Studies
Bing Ren: Ludwig Institute for Cancer Research

Nature Communications, 2021, vol. 12, issue 1, 1-15

Abstract: Abstract Identification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.

Date: 2021
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DOI: 10.1038/s41467-021-21583-9

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