ArticleAmerican journal of human genetics2023
Fast and accurate Bayesian polygenic risk modeling with variational inference.
Article in American journal of human genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genetic Biomarkers for Periodontal Diseases: A Systematic Review.Journal of clinical periodontology · 2025Pooled it
- Improved polygenic risk prediction for alzheimer's disease and related dementias using deep learning: age and APOE-stratified analysis.Alzheimer's research & therapy · 2026Article
- Topological stratification of continuous genetic variation in large biobanks.PLoS genetics · 2026Article
- Polygenic risk scores: Navigating the future of precision medicine through economic, ethical, and scientific advancements.iScience · 2026Review
- Statistical construction of calibrated prediction intervals for polygenic score-based phenotype prediction.Nature genetics · 2025Article
- Sparse polygenic risk score inference with the spike-and-slab LASSO.Bioinformatics (Oxford, England) · 2025Article
- Sex-Specific Polygenic Risk Scores and Replication in a Model-Free Analysis of Schizophrenia Data.Genes · 2025Article
- Improvement of polygenic modeling of blood pressure traits using lifestyle information in the UK Biobank.Genetics · 2025Article
- Toward whole-genome inference of polygenic scores with fast and memory-efficient algorithms.American journal of human genetics · 2025Article
- EndoPRS: Incorporating endophenotype information to improve polygenic risk scores for clinical endpoints-A study in asthma.American journal of human genetics · 2025Article
- Analysis-ready VCF at Biobank scale using Zarr.bioRxiv : the preprint server for biology · 2025Article
- Analysis-ready VCF at Biobank scale using Zarr.GigaScience · 2025Article
- Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes.PLoS genetics · 2025Article
- GWASBrewer: An R Package for Simulating Realistic GWAS Summary Statistics.Genetic epidemiology · 2025Article
- Advancements and limitations in polygenic risk score methods for genomic prediction: a scoping review.Human genetics · 2024Article
- Parkinson's Disease Polygenic Risk Score and Neurological Involvement in Carriers of the FMR1 Premutation Allele: A Case for Genetic Modifier.Molecular genetics & genomic medicine · 2024Article
- Finemap-MiXeR: A variational Bayesian approach for genetic finemapping.PLoS genetics · 2024Article
- Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes.bioRxiv : the preprint server for biology · 2024Article
- A linear weighted combination of polygenic scores for a broad range of traits improves prediction of coronary heart disease.European journal of human genetics : EJHG · 2024Article
- Power of inclusion: Enhancing polygenic prediction with admixed individuals.American journal of human genetics · 2023Article
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3 authors.
Funding
Abstract
The advent of large-scale genome-wide association studies (GWASs) has motivated the development of statistical methods for phenotype prediction with single-nucleotide polymorphism (SNP) array data. These polygenic risk score (PRS) methods use a multiple linear regression framework to infer joint effect sizes of all genetic variants on the trait. Among the subset of PRS methods that operate on GWAS summary statistics, sparse Bayesian methods have shown competitive predictive ability. However, most existing Bayesian approaches employ Markov chain Monte Carlo (MCMC) algorithms, which are computationally inefficient and do not scale favorably to higher dimensions, for posterior inference. Here, we introduce variational inference of polygenic risk scores (VIPRS), a Bayesian summary statistics-based PRS method that utilizes variational inference techniques to approximate the posterior distribution for the effect sizes. Our experiments with 36 simulation configurations and 12 real phenotypes from the UK Biobank dataset demonstrated that VIPRS is consistently competitive with the state-of-the-art in prediction accuracy while being more than twice as fast as popular MCMC-based approaches. This performance advantage is robust across a variety of genetic architectures, SNP heritabilities, and independent GWAS cohorts. In addition to its competitive accuracy on the "White British" samples, VIPRS showed improved transferability when applied to other ethnic groups, with up to 1.7-fold increase in R
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.