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; Bing Ren · 2021 · Nature Communications
Paper
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.
Analysis
SnapATAC is a new software package designed to analyze single-cell ATAC-seq data, overcoming noise and data volume challenges to identify regulatory elements and infer transcriptional regulators across diverse cell populations.
Discovery
Ngo J; Lee E; Olah M; Sher F
Kidder BL
Wanfeng Lu; Yutong Zhang; Keyi Zhou; Chenxin Ge; Wei Lin; Qunxi Zhu
Xiao Xiao; Jiashu He; Shiyang Zhang; Meiyi Mao
Olga lanzetta; Luisa Cutillo; Bailey Andrew; Claudia Angelini
Suvojit Hazra; Chandrani Kumari; Sushmita Roy
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