Article

A machine-learning framework to characterize functional disease architectures and prioritize disease variants

2025-10-24

Abstract excerpt

Modeling disease effect sizes from genome-wide association studies (GWAS) is critical for both advancing our understanding of the functional architecture of human disease and providing informative priors that enhance the prioritization of potentially causal variants. Here, we introduce the variant-to-disease (V2D) framework, an approach that leverages machine-learning algorithms to model disease effect sizes from...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 3e1a5707-55b5-5e1a-ada2-bafb901ca7af
DOI: 10.1101/2025.10.23.25338598

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A machine-learning framework to characterize functional disease architectures and prioritize disease variantsDOI 10.1101/2025.10.23.25338598Read

A machine-learning framework to characterize functional disease architectures and prioritize disease variantsSemantic proximity Read

A consensus variant-to-function score to functionally prioritize variants for diseaseSemantic proximity Read

Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets.Semantic proximity Read

Evaluating the informativeness of deep learning annotations for human complex diseasesSemantic proximity Read

Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity.Semantic proximity Read

Integrative approaches to improve the informativeness of deep learning models for human complex diseasesSemantic proximity Read

Leverage Large-Scale Biological Networks to Decipher the Genetic Basis of Human Diseases Using Machine Learning.Semantic proximity Read

Evaluating the informativeness of deep learning annotations for human complex diseases.Semantic proximity Read

Disease-specific prioritization of non-coding GWAS variants based on chromatin accessibilitySemantic proximity Read

An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci.Semantic proximity Read

Disease-specific prioritization of non-coding GWAS variants based on chromatin accessibility.Semantic proximity Read

Leveraging functional annotations in genetic risk prediction for human complex diseases.Semantic proximity Read