AI Article Synopsis
- Identifying cis-regulatory elements is key to understanding cellular diversity, but analyzing primary tissues is complicated by sample variability.
- Single-cell ATAC-seq (scATAC-seq) helps address this by analyzing open chromatin at the single-cell level, though it introduces computational challenges due to data noise and volume.
- SnapATAC is a new software tool designed to analyze scATAC-seq data efficiently, allowing for unbiased exploration of cellular diversity and identification of around 370,000 regulatory elements across 31 cell types in the mouse brain.
Article 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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910485 | PMC |
| http://dx.doi.org/10.1038/s41467-021-21583-9 | DOI Listing |
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