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Classifying cells with Scasat, a single-cell ATAC-seq analysis tool.

ABSTRACT: ATAC-seq is a recently developed method to identify the areas of open chromatin in a cell. These regions usually correspond to active regulatory elements and their location profile is unique to a given cell type. When done at single-cell resolution, ATAC-seq provides an insight into the cell-to-cell variability that emerges from otherwise identical DNA sequences by identifying the variability in the genomic location of open chromatin sites in each of the cells. This paper presents Scasat (single-cell ATAC-seq analysis tool), a complete pipeline to process scATAC-seq data with simple steps. Scasat treats the data as binary and applies statistical methods that are especially suitable for binary data. The pipeline is developed in a Jupyter notebook environment that holds the executable code along with the necessary description and results. It is robust, flexible, interactive and easy to extend. Within Scasat we developed a novel differential accessibility analysis method based on information gain to identify the peaks that are unique to a cell. The results from Scasat showed that open chromatin locations corresponding to potential regulatory elements can account for cellular heterogeneity and can identify regulatory regions that separates cells from a complex population.

SUBMITTER: Baker SM

PROVIDER: S-EPMC6344856 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Classifying cells with Scasat, a single-cell ATAC-seq analysis tool.

Baker Syed Murtuza SM Rogerson Connor C Hayes Andrew A Sharrocks Andrew D AD Rattray Magnus M

Nucleic acids research 20190101 2

ATAC-seq is a recently developed method to identify the areas of open chromatin in a cell. These regions usually correspond to active regulatory elements and their location profile is unique to a given cell type. When done at single-cell resolution, ATAC-seq provides an insight into the cell-to-cell variability that emerges from otherwise identical DNA sequences by identifying the variability in the genomic location of open chromatin sites in each of the cells. This paper presents Scasat (single ...[more]

PMID: 30335168

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Project description:PurposeCorneal epithelial homeostasis is maintained by coordinated gene expression across distinct cell populations, but the gene regulatory programs underlying this cellular diversity remain to be characterized. Here we applied single-cell multi-omics analysis to delineate the gene regulatory profile of mouse corneal epithelial cells under normal homeostasis.MethodsSingle cells isolated from the cornea epithelium (with marginal conjunctiva) of adult mice were subjected to scRNA-seq and scATAC-seq using the 10×Genomics platform. Cell types were clustered by the graph-based visualization method uniform manifold approximation and projection and unbiased computational informatics analysis. The scRNA-seq and scATAC-seq datasets were integrated following the integration pipeline described in ArchR and Seurat.ResultsWe characterized diverse corneal epithelial cell types based on gene expression signatures and chromatin accessibility. We found that cell type-specific accessibility regions were mainly located at distal regions, suggesting essential roles of distal regulatory elements in determining corneal epithelial cell diversity. Trajectory analyses revealed a continuum of cell state transition and higher coordination between transcription factor (TF) motif accessibility and gene expression during corneal epithelial cell differentiation. By integrating transcriptomic and chromatin accessibility analysis, we identified cell type-specific and shared gene regulation programs. We also uncovered critical TFs driving corneal epithelial cell differentiation, such as nuclear factor I (NFI) family members, Rarg, Elf3. We found that nuclear factor-κB (NF-κB) family members were positive TFs in limbal cells and some superficial cells, but they were involved in regulating distinct biological processes.ConclusionsOur study presents a comprehensive gene regulatory landscape of mouse cornea epithelial cells, and provides valuable foundations for future investigation of corneal epithelial homeostasis in the context of cornea pathologies and regenerative medicine.

Dataset Information

Classifying cells with Scasat, a single-cell ATAC-seq analysis tool.

Publications

Classifying cells with Scasat, a single-cell ATAC-seq analysis tool.

Similar Datasets

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