PennPRS: a centralized cloud computing platform for efficient polygenic risk score training in precision medicine

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

Polygenic risk scores (PRS) are becoming increasingly vital for prediction and stratification in precision medicine. However, PRS model training presents significant challenges broader adoption of PRS, including limited access to computational resources, difficulties implementing advanced methods, availability privacy concerns over individual-level genetic data. Cloud computing provides a promising solution with centralized data resources. Here we introduce PennPRS ( https://pennprs.org ), scalable cloud platform online We developed novel pseudo-training algorithms multiple methods ensemble approaches, enabling without requiring These were rigorously validated through extensive simulations large-scale real analyses involving 6,000 phenotypes across various sources. supports single- multi-ancestry seven allowing users upload their own or query from more than 27,000 datasets the GWAS Catalog, submit jobs, download trained models. Additionally, applied our pipeline train models 8,000 made weights publicly accessible. In summary, improve accessibility applications reduce disparities resources global research community.

Язык: Английский

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EndoPRS: Incorporating endophenotype information to improve polygenic risk scores for clinical endpoints—A study in asthma

The American Journal of Human Genetics, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

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Precision oncology and genetic ancestry: The science behind population-based cancer disparities

Cancer Cell, Год журнала: 2025, Номер 43(4), С. 619 - 622

Опубликована: Апрель 1, 2025

Язык: Английский

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