Risk Prediction Modeling on Family-Based Sequencing Data Using a Random Field Method.

ABSTRACT: Family-based design is one of the most popular designs in genetic studies and has many unique features for risk-prediction research. It is robust against genetic heterogeneity, and the relatedness among family members can be informative for predicting an individual's risk for disease with polygenic and shared environmental components of risk. Despite these strengths, family-based designs have been used infrequently in current risk-prediction studies, and their related statistical methods have not been well developed. In this article, we developed a generalized random field (GRF) method for family-based risk-prediction modeling on sequencing data. In GRF, subjects' phenotypes are viewed as stochastic realizations of a random field in a space, and a subject's phenotype is predicted by adjace

SUBMITTER: Wen Y 

PROVIDER: S-EPMC5586386 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature