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

XPXP: improving polygenic prediction by cross-population and cross-phenotype analysis.

Bioinformatics (Oxford, England) - 28 Mar 2022

Xiao Jiashun, Cai Mingxuan, Hu Xianghong, Wan Xiang, Chen Gang, Yang Can

Abstract excerpt

MOTIVATION: As increasing sample sizes from genome-wide association studies (GWASs), polygenic risk scores (PRSs) have shown great potential in personalized medicine with disease risk prediction, prevention and treatment. However, the PRS constructed using European samples becomes less accurate when it is applied to individuals from non-European populations. It is an urgent task to improve the accuracy of PRSs in...

Read the complete abstract on PubMed

Topics

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

Share to Diabetes Mellitus, Type 2
Share to Genome-Wide Association Study

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Multifactorial Inheritance

Share to Phenotype

Share to Polymorphism, Single Nucleotide

Source

Identifiers

PMID: 35040939
DOI: 10.1093/bioinformatics/btac029

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

XPXP: improving polygenic prediction by cross-population and cross-phenotype analysis.PMID 35040939Read ↗

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

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

SDPRX: A statistical method for cross-population prediction of complex traits.Semantic proximity Read ↗

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

Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores.Semantic proximity Read ↗

Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statisticsSemantic proximity Read ↗

Multiethnic polygenic risk scores improve risk prediction in diverse populations.Semantic proximity Read ↗

Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics.Semantic proximity Read ↗

Leveraging pleiotropy to improve genetic risk prediction across diseasesSemantic proximity Read ↗

Assessment of polygenic risk score performance in East Asian populations for ten common diseasesSemantic proximity Read ↗

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

Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.Semantic proximity Read ↗

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