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

Generalizability of polygenic prediction models: how is the R2 defined on test data?

BMC medical genomics - 16 May 2024

Staerk Christian, Klinkhammer Hannah, Wistuba Tobias, Maj Carlo, Mayr Andreas

Abstract excerpt

BACKGROUND: Polygenic risk scores (PRS) quantify an individual's genetic predisposition for different traits and are expected to play an increasingly important role in personalized medicine. A crucial challenge in clinical practice is the generalizability and transferability of PRS models to populations with different ancestries. When assessing the generalizability of PRS models for continuous traits, the R 2 is...

Read the complete abstract on PubMed

Topics

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

Share to Genetic Predisposition to Disease
Share to Models, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Multifactorial Inheritance

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 38755654
DOI: 10.1186/s12920-024-01905-8
PMCID: PMC11100126

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Generalizability of polygenic prediction models: how is the R2 defined on test data?PMID 38755654Read ↗

Beyond predictive R2: Quantile regression and non-equivalence tests reveal complex relationships of traits and polygenic scores.Semantic proximity Read ↗

Cross-Ancestry Polygenic Prediction: Comparing Methods and Assessing Transferability Across Traits.Semantic proximity Read ↗

Significance tests for R2 of out-of-sample prediction using polygenic scores.Semantic proximity Read ↗

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores.Semantic proximity Read ↗

Principles and methods for transferring polygenic risk scores across global populations.Semantic proximity Read ↗

Polygenic risk score prediction accuracy convergenceSemantic proximity Read ↗

Multi-ethnic polygenic risk scores improve risk prediction in diverse populationsSemantic proximity Read ↗

Integrative polygenic risk score improves the prediction accuracy of complex traits and diseasesSemantic proximity Read ↗

Polygenic risk score portability for common diseases across genetically diverse populationsSemantic proximity Read ↗

Benchmarking Polygenic Risk Score Model Assumptions: towards more accurate risk assessmentSemantic proximity Read ↗

Correlation-based tests for the formal comparison of polygenic scores in multiple populations.Semantic proximity Read ↗

Advancements and limitations in polygenic risk score methods for genomic prediction: a scoping review.Semantic proximity Read ↗

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