Two‐phase designs for joint quantitative‐trait‐dependent and genotype‐dependent sampling in post‐GWAS regional sequencing. Issue 1 (14th December 2017)

• Record Type: Journal Article
• Authors: Espin‐Garcia, Osvaldo; Craiu, Radu V.; Bull, Shelley B.
• Is Part Of: Genetic epidemiology. Volume 42:Issue 1(2018)
• Page Start: 104
• Page End: 116
• Publication Date: 2017-12-14
• Subjects: fine‐mapping -- Genetic Analysis Workshop 19 -- genetic association studies -- joint outcome covariate dependent sampling -- outcome‐/covariate‐dependent sampling; Genetic epidemiology -- Periodicals; Heredity -- Periodicals; Medical geography -- Periodicals; 614
• DOI: 10.1002/gepi.22099
• Languages: English
• ISSNs: 0741-0395

Abstract

ABSTRACT: We evaluate two‐phase designs to follow‐up findings from genome‐wide association study (GWAS) when the cost of regional sequencing in the entire cohort is prohibitive. We develop novel expectation‐maximization‐based inference under a semiparametric maximum likelihood formulation tailored for post‐GWAS inference. A GWAS‐SNP (where SNP is single nucleotide polymorphism) serves as a surrogate covariate in inferring association between a sequence variant and a normally distributed quantitative trait (QT). We assess test validity and quantify efficiency and power of joint QT‐SNP‐dependent sampling and analysis under alternative sample allocations by simulations. Joint allocation balanced on SNP genotype and extreme‐QT strata yields significant power improvements compared to marginal QT‐ or SNP‐based allocations. We illustrate the proposed method and evaluate the sensitivity of sample allocation to sampling variation using data from a sequencing study of systolic blood pressure.