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RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Jan 18, 2026

ATAC-Seq Optimization for Cancer Epigenetics Research

ATAC-Seq Optimization for Cancer Epigenetics Research

Published on: June 30, 2022

Developing a comprehensive database and search tool for single-cell ATAC-seq data.

Arrian Gibson-Khademi^1,2, Jonathan Wang^1,2, Erik Christensen^2,3

¹Department of Pathology and Lab Medicine, University of Western Ontario, London, ON, N6A 5C1, Canada.

Scientific Reports

|January 16, 2026

Summary

This summary is machine-generated.

Researchers have developed scATAC.Explorer, a new database for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data. This tool provides a centralized, searchable collection of scATAC-seq datasets to advance gene regulation studies.

Keywords:

Chromatin accessibility Database and search tool Single-cell sequencing scATAC-seq

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) enables chromatin accessibility analysis at single-cell resolution.
scATAC-seq is crucial for understanding gene regulation in cell development and disease.
Existing scATAC-seq data is fragmented, lacking a unified, consistently formatted database.

Purpose of the Study:

To create a comprehensive, accessible database of publicly available scATAC-seq datasets.
To provide a search tool for efficient retrieval and analysis of scATAC-seq data.
To facilitate multi-dataset analysis in R and Python environments.

Main Methods:

Developed scATAC.Explorer, an R-accessible database and search tool.
Curated a collection of 39 scATAC-seq datasets from diverse tissues and cell types.
Integrated accessibility matrices, cell type annotations, and metadata for each dataset.

Main Results:

scATAC.Explorer offers fast query and retrieval of scATAC-seq datasets.
The database contains consistent formatting for 39 diverse scATAC-seq datasets.
The tool is available via GitHub and as an R Bioconductor package.

Conclusions:

scATAC.Explorer addresses the need for a unified scATAC-seq data repository.
The database and search tool streamline analysis of single-cell chromatin accessibility data.
Facilitates integration into existing R and Python workflows for broader research application.