ArticleDatabase : the journal of biological databases and curation2026
scRiskDB: a single-cell epigenomic resource linking complex traits to regulatory mechanisms across human tissues.
Article in Database : the journal of biological databases and curation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the regulatory impact of non-coding genetic variants remains a major challenge in human genetics. Here, we present scRiskDB, a comprehensive and user-friendly database that maps genetic risk variants to their downstream regulatory elements, target genes, and relevant cell types at single-cell resolution. By integrating genome-wide association studies (GWAS) with single-cell datasets across 45 tissues and developmental stages, scRiskDB implements a variant-to-function framework that systematically outlines potential regulatory cascades from single nucleotide variants to cell-specific risk mechanisms. This multi-layered design allows users to explore trait-associated regulatory architectures across cell types and developmental stages. The platform provides interactive, multi-level visualizations and curated results, facilitating hypothesis generation and mechanistic insights into disease aetiology.
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.