Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Whole-genome sequencing analysis of anthropometric traits in 672,976 individuals reveals convergence between rare and common genetic associations

bioRxiv (Cold Spring Harbor Laboratory)(2025)10.1101/2025.02.24.639925Source: DataRank Database

Whole-genome sequencing analysis of anthropometric traits in 672,976 individuals reveals convergence between rare and common genetic associations is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2025). On theSindex it has a DataRank of 0. It has been cited 3 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access3 citations

Download PDF

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)OA: greenTopics (19)IDs (PubMed)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (12)

Harrison I. W. Wright,Robin N. Beaumont ORCID,V. Kartik Chundru ORCID,Aimee Hanson ORCID,Leigh Jackson ORCID

Live enrichment

PubMed:19162232

Wellcome Trust

Grant: unidentified

unidentified

UK Research and Innovation

Grant: MR/M008924/1

Accelerated discovery of functional non-coding genomic variation using single molecule real-time (SMRT) sequencing.

UK Research and Innovation

Grant: MR/T002239/1

Using genetics to test the disease consequences of higher adiposity uncoupled from its adverse metabolic effects

UK Research and Innovation

Grant: MR/Y003748/1

Using whole genome sequencing to identify non-coding elements associated with diabetes and related traits across ancestries

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2025/02/25/2025.02.24.639925.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2025.02.24.639925

Unpaywallhttps://doi.org/10.1101/2025.02.24.639925

Europe_PMChttps://europepmc.org/article/PPR/PPR982514

Europe_PMChttps://europepmc.org/api/fulltextRepo?pprId=PPR982514&type=FILE&fileName=EMS203605-pdf.pdf&mimeType=application/pdf

Fields of Study

0301 basic medicine03 medical and health sciences

Keywords

MaleAdultWhole Genome SequencingAnthropometryWaist-Hip RatioQuantitative Trait LociMiddle AgedPolymorphism, Single NucleotideArticleBody HeightUnited KingdomBody Mass IndexFibroblast Growth FactorsHumansFemaleGenome-Wide Association StudyAged