ReviewCell genomics2023
Aligning NIH's existing data use restrictions to the GA4GH DUO standard.
Review in Cell genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- Characterizing core outcomes of responsible stewardship for human genomic data in the cloud.BMC medical genomics · 2026Article
- Toward Responsible and Sustainable Data Sharing in Large-scale Cohort-based Genomic Research.Genomics, proteomics & bioinformatics · 2025Article
- A call to action to scale up research and clinical genomic data sharing.Nature reviews. Genetics · 2025Review
- A qualitative interview study to determine barriers and facilitators of implementing automated decision support tools for genomic data access.BMC medical ethics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is widely accepted that large-scale genomic data (e.g., whole-genome sequencing, whole-exome sequencing, and genome-wide association study data) be shared through a controlled-access mechanism. This protects the privacy of research participants and ensures downstream uses of data align with participants' informed consent regarding future sharing of their data. In 2019, GA4GH approved the Data Use Ontology (DUO) standard to define data use terms with machine-readable representations to represent how a dataset can be used. We endeavored to determine the parity of existing data use restrictions ("Data Use Limitations" [DULs]) for datasets registered in the National Institutes of Health database for Genotypes and Phenotypes (dbGaP) with the DUO standard. We found substantial (93%) parity between the dbGaP DULs (n = 3,575) and DUO. This study demonstrates the comprehensiveness of the DUO standard and encourages data stewards to standardize data use restrictions in machine-readable formats to facilitate data sharing.
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.