Evidence map›Paper›PMID 41545440›Full record

ArticleScientific reports2026

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

Arrian Gibson-Khademi, Jonathan Wang, Erik Christensen, Parisa Shooshtari

Abstract read
In one paragraph

Article in Scientific reports, 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. Article
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

4 authors.

Arrian Gibson-KhademiDepartment of Pathology and Lab Medicine, University of Western Ontario, London, ON, N6A 5C1, Canada.
Jonathan WangDepartment of Pathology and Lab Medicine, University of Western Ontario, London, ON, N6A 5C1, Canada.
Erik ChristensenChildren's Health Research Institute, London Health Sciences Centre Research Institute (LHSCRI), A5-144, 800 Commissioners Road East, London, ON, N6C 2R5, Canada.
Parisa ShooshtariDepartment of Pathology and Lab Medicine, University of Western Ontario, London, ON, N6A 5C1, Canada. pshoosh@uwo.ca.

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN/04062-2021 and DGECR-2021-00298
6 · The paper itself

Abstract

Single cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is a technology that allows for analysis of chromatin accessibility at a single cell resolution. scATAC-seq is advancing our understanding of gene regulation, and has found many applications in cell development and disease. Despite the availability of several scATAC-seq datasets and their high applicability, we still lack a definitive scATAC-seq database, where a comprehensive collection of publicly available scATAC-seq datasets has been made available in a consistent format. To solve this, we have created scATAC.Explorer, an R accessible database and search tool, containing a curated collection of 39 currently available scATAC-seq datasets from a wide array of tissues and cell types. scATAC.Explorer allows fast query and retrieval of publicly available scATAC-seq datasets, and it contains accessibility matrices, cell type annotations and other metadata information for each dataset. scATAC.Explorer is available both in GitHub and as an R Bioconductor package, and can easily be integrated into existing R and Python analysis pipelines, allowing researchers to quickly analyze scATAC-seq data from multiple sources.

Indexed as

Chromatin Immunoprecipitation SequencingDatabases, GeneticSingle-Cell AnalysisSoftwareAnimalsBiocurationChromatinComputational BiologyHumansTransposasesChromatinTransposasesChromatin accessibilityDatabase and search toolscATAC-seqSingle-cell sequencing

Identifiers

PMID41545440
PMCPMC12816011

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.