| Literature DB >> 33637727 |
Rongxin Fang1,2, Sebastian Preissl3, Yang Li1, Xiaomeng Hou3, Jacinta Lucero4, Xinxin Wang3, Amir Motamedi5, Andrew K Shiau5, Xinzhu Zhou6, Fangming Xie7, Eran A Mukamel7, Kai Zhang1, Yanxiao Zhang1, M Margarita Behrens4, Joseph R Ecker4,8, Bing Ren9,10,11.
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.Entities:
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Year: 2021 PMID: 33637727 PMCID: PMC7910485 DOI: 10.1038/s41467-021-21583-9
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919