Journal
NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41467-021-21583-9
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Funding
- Damon Runyon Cancer Research Foundation [DRG- 2433-21]
- NIH [1K99CA252020-01]
- UCSD School of Medicine
- [U19MH114831]
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The paper introduces SnapATAC, a software package for analyzing single cell ATAC-seq datasets, which can dissect cellular heterogeneity and map cellular states' trajectories. The Nystrom method allows processing data from up to a million cells, and it incorporates existing tools for single cell ATAC-seq dataset analysis. SnapATAC is applied to mouse secondary motor cortex profiles and identifies candidate regulatory elements and cell-type specific transcriptional regulators.
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 Nystrom 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 similar to 370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.
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