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

Contextualizing genetic risk score for disease screening and rare variant discovery.

Nature communications - 20 Jul 2021

Zhou Dan, Yu Dongmei, Scharf Jeremiah M, Mathews Carol A, McGrath Lauren, Cook Edwin, Lee S Hong, Davis Lea K, Gamazon Eric R

Abstract excerpt

Studies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive...

Read the complete abstract on PubMed

Topics

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

Share to Clinical Decision-Making
Share to Datasets as Topic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetic Testing

Share to Genome-Wide Association Study

Share to Models, Genetic

Share to Multifactorial Inheritance

Share to Software

Share to Whole Genome Sequencing

Source

Open in PubMed Open full text

Identifiers

PMID: 34285202
DOI: 10.1038/s41467-021-24387-z
PMCID: PMC8292385

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Contextualizing genetic risk score for disease screening and rare variant discovery.PMID 34285202Read ↗

Rare-variant risk scores complement common-variant polygenic scores for disease risk prediction and stratificationSemantic proximity Read ↗

STELLAR: A flexible ensemble learning framework integrating rare variants to enhance polygenic risk predictionSemantic proximity Read ↗

Flexibly Modeling Rare Variant Pathogenicity Improves Gene Discovery for Complex TraitsSemantic proximity Read ↗

Integrating common and rare variants improves polygenic risk prediction across diverse populations.Semantic proximity Read ↗

Estimation of complex effect-size distributions using summary-level statistics from genome-wide association studies across 32 complex traits.Semantic proximity Read ↗

Rare penetrant mutations confer severe risk of common diseasesSemantic proximity Read ↗

Rare penetrant mutations confer severe risk of common diseases.Semantic proximity Read ↗

Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR.Semantic proximity Read ↗

Causal variant capture in genotype discovery approaches drives polygenic prediction performance across traits and populationsSemantic proximity Read ↗

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

Individuals with common diseases but with a low polygenic risk score could be prioritized for rare variant screening.Semantic proximity Read ↗

The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease.Semantic proximity Read ↗

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