Improving polygenic prediction from whole-genome sequencing data by leveraging predicted epigenomic features
Zeng W, Guo H, Liu Q, Wong H. Improving polygenic prediction from whole-genome sequencing data by leveraging predicted epigenomic features. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2419202122. PMID: 40504151, PMCID: PMC12184400, DOI: 10.1073/pnas.2419202122.Peer-Reviewed Original ResearchConceptsWhole-genome sequencingWhole-genome sequencing dataPolygenic risk scoresVariant effectsIndividual susceptibility to complex diseasesAdvent of whole-genome sequencingSusceptibility to complex diseasesPolygenic risk score approachPolygenic risk score performanceRare variant effectsComplex genetic architecturePolygenic risk score methodsDe novo variantsEpigenomic contextEpigenomic featuresGenomic regionsGenetic architectureSequence dataEpigenomic signalsVariant contributionsPolygenic predictionVariant impactDiploid genotypesGenetic variantsDisease risk prediction
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