Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank.

Nature genetics - 1 Sept 2017

Cortes Adrian, Dendrou Calliope A, Motyer Allan, Jostins Luke, Vukcevic Damjan, Dilthey Alexander, Donnelly Peter, Leslie Stephen, Fugger Lars, McVean Gil

Abstract excerpt

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data can transform understanding of the human phenome and accelerate progress toward precision medicine. However, a critical question when analyzing high-dimensional and heterogeneous data is how best to interrogate increasingly specific subphenotypes while retaining statistical power to detect genetic associations. Here we...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Bayes Theorem
Share to Cluster Analysis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Delivery of Health Care

Share to Genetic Association Studies

Share to HLA Antigens

Share to International Classification of Diseases

Share to Logistic Models

Share to United Kingdom

Source

Open in PubMed Open full text

Identifiers

PMID: 28759005
DOI: 10.1038/ng.3926
PMCID: PMC5580804

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank.PMID 28759005Read ↗

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK BiobankSemantic proximity Read ↗

Identifying cross-disease components of genetic risk across hospital data in the UK Biobank.Semantic proximity Read ↗

Disease prediction with multi-omics and biomarkers empowers case-control genetic discoveries in the UK Biobank.Semantic proximity Read ↗

Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK BiobankSemantic proximity Read ↗

A global atlas of genetic associations of 220 deep phenotypesSemantic proximity Read ↗

Computationally efficient methods for estimating phenome-wide coheritability of multi-type phenotypes using biobank data.Semantic proximity Read ↗

Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseasesSemantic proximity Read ↗

Age-dependent topic modelling of comorbidities in UK Biobank identifies disease subtypes with differential genetic riskSemantic proximity Read ↗

Applying Machine Learning on UK Biobank biomarker data empowers case-control discovery yieldSemantic proximity Read ↗

Incorporating phenotype heterogeneity in disease GWAS improves power while maintaining specificitySemantic proximity Read ↗

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology.Semantic proximity Read ↗

Exploring the genetic architecture of multiple long-term conditions using a genome-wide association study in the UK Biobank population.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.