Evidence map›Paper›PMID 41296545›Full record

ArticleNucleic acids research2026

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

Xiaoyang Chen, Zijing Gao, Keyi Li, Zian Wang, Qun Jiang, Xuejian Cui, Zhen Li, Rui Jiang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xiaoyang ChenMinistry 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.ORCID 0000-0002-7356-8129
Zijing GaoMinistry 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.ORCID 0009-0005-7269-0244
Keyi LiMinistry 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.ORCID 0009-0009-6880-2433
Zian WangMinistry 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.
Qun JiangMinistry 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.
Xuejian CuiMinistry 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.
Zhen LiMinistry 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.ORCID 0000-0002-3013-3416
Rui JiangMinistry 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.ORCID 0000-0002-7533-3753

Funding

Beijing Natural Science Foundation L242026National Key Research and Development Program of China 2021YFF1200902National Key Research and Development Program of China 2023YFF1204802National Key Research and Development Program of China 2025YFC3409300National Natural Science Foundation of China 62 273 194National Natural Science Foundation of China 62273194
6 · The paper itself

Abstract

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) profiles chromatin accessibility at cellular resolution, making it possible to reveal epigenomic landscapes that govern gene regulation in a variety of cells. Nevertheless, heterogeneous feature spaces and complex processing pipelines have impeded the construction of an ensemble resource capable of supporting diverse downstream analytical scenarios. To address this gap, we present Human-scATAC-Corpus (https://health.tsinghua.edu.cn/human-scatac-corpus/), a comprehensive database of human scATAC-seq comprising 5 407 621 cells from 35 datasets across 37 tissues or cell lines. To support complementary use cases, each dataset is distributed in three aligned formats: cell-by-candidate cis-regulatory element matrices for cross-dataset integration, raw fragment files for flexible processing, and cell-by-peak matrices for within-dataset analyses. This resource spans diverse biological contexts and includes rich metadata, enabling method benchmarking and development, as well as pretraining of foundation models. The website offers searchable browsing, detailed dataset pages, on-demand downloads, and tutorials. EpiAgent, a foundation model pretrained on Human-scATAC-Corpus, is further integrated to provide online analyses, including reference mapping, embedding extraction, and cell type annotation. Human-scATAC-Corpus establishes a unified and scalable substrate for single-cell epigenomics and is intended to accelerate discovery while standardizing evaluation across tasks.

Indexed as

ChromatinDatabases, GeneticSingle-Cell AnalysisEpigenomicsHigh-Throughput Nucleotide SequencingHumansInternetSequence Analysis, DNASoftwareTransposasesChromatinTransposases

Identifiers

PMID41296545
PMCPMC12807747

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.