Ontology highlight
ABSTRACT:
SUBMITTER: Elgart M
PROVIDER: S-EPMC9395509 | biostudies-literature | 2022 Aug
REPOSITORIES: biostudies-literature
Elgart Michael M Lyons Genevieve G Romero-Brufau Santiago S Kurniansyah Nuzulul N Brody Jennifer A JA Guo Xiuqing X Lin Henry J HJ Raffield Laura L Gao Yan Y Chen Han H de Vries Paul P Lloyd-Jones Donald M DM Lange Leslie A LA Peloso Gina M GM Fornage Myriam M Rotter Jerome I JI Rich Stephen S SS Morrison Alanna C AC Psaty Bruce M BM Levy Daniel D Redline Susan S Sofer Tamar T
Communications biology 20220822 1
Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a trait, yet they fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). We address this via a machine learning approach, validated in nine complex phenotypes in a multi-ancestry population. We use an ensemble method of SNP selection followed by gradient boosted trees (XGBoost) to allow for non-linearities and interaction effects. We compare our results to th ...[more]