ArticleScientific reports2026
Developing a comprehensive database and search tool for single-cell ATAC-seq data.
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.
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.
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.
Who cites it
1 citing paper in PubMed.
- DNA methylation and gene expression signatures for common childhood infections.Clinical epigenetics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
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
Identifiers
What OpenQuestion holds
Registered trials
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.