Bayesian linear mixed model with multiple random effects for family-based genetic studies.

ABSTRACT: Motivation: Family-based study design is one of the popular designs used in genetic research, and the whole-genome sequencing data obtained from family-based studies offer many unique features for risk prediction studies. They can not only provide a more comprehensive view of many complex diseases, but also utilize information in the design to further improve the prediction accuracy. While promising, existing analytical methods often ignore the information embedded in the study design and overlook the predictive effects of rare variants, leading to a prediction model with sub-optimal performance. Results: We proposed a Bayesian linear mixed model for the prediction analysis of sequencing data obtained from family-based studies. Our method can not only capture predictive effec

SUBMITTER: Hai Y 

PROVIDER: S-EPMC10620972 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature