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Updated: Jan 10, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Human-scATAC-Corpus: a comprehensive database of scATAC-seq data.

Xiaoyang Chen¹, Zijing Gao¹, Keyi Li¹

¹Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing100084, China.

Nucleic Acids Research

|November 26, 2025

Summary

This summary is machine-generated.

We developed Human-scATAC-Corpus, a large database of human single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data. This resource unifies epigenomic landscapes for diverse downstream analyses and foundation model pretraining.

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

Published on: October 5, 2018

Area of Science:

Genomics
Epigenetics
Computational Biology

Background:

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) provides cellular resolution of chromatin accessibility.
Heterogeneous data and complex pipelines hinder the creation of unified epigenomic resources.
Existing resources lack comprehensive integration for diverse analytical needs.

Purpose of the Study:

To establish a comprehensive, unified, and scalable database of human scATAC-seq data.
To facilitate diverse downstream analyses, method development, and foundation model pretraining.
To provide a standardized platform for evaluating single-cell epigenomic analyses.

Main Methods:

Compilation of 5,407,621 cells from 35 scATAC-seq datasets across 37 human tissues/cell lines.
Distribution of data in three aligned formats: cell-by-candidate cis-regulatory element matrices, raw fragment files, and cell-by-peak matrices.
Integration of EpiAgent, a foundation model pretrained on the corpus for online analyses.

Main Results:

Creation of Human-scATAC-Corpus, a large-scale database of human scATAC-seq data.
Provision of data in multiple formats supporting cross-dataset integration, flexible processing, and within-dataset analysis.
Demonstration of the resource's utility for method benchmarking, foundation model pretraining, and online analysis via EpiAgent.

Conclusions:

Human-scATAC-Corpus provides a unified and scalable foundation for human single-cell epigenomics.
The database accelerates discovery and standardizes evaluation in single-cell epigenomic research.
The integrated EpiAgent enables advanced online analyses, enhancing resource accessibility and utility.