Weighted pseudolikelihood for SNP set analysis with multiple secondary outcomes in case-control genetic association studies.

ABSTRACT: We propose a weighted pseudolikelihood method for analyzing the association of a SNP set, example, SNPs in a gene or a genetic pathway or network, with multiple secondary phenotypes in case-control genetic association studies. To boost analysis power, we assume that the SNP-specific effects are shared across all secondary phenotypes using a scaled mean model. We estimate regression parameters using Inverse Probability Weighted (IPW) estimating equations obtained from the weighted pseudolikelihood, which accounts for case-control sampling to prevent potential ascertainment bias. To test the effect of a SNP set, we propose a weighted variance component pseudo-score test. We also propose a penalized IPW pseudolikelihood method for selecting a subset of SNPs that are associated with the multip

SUBMITTER: Sofer T 

PROVIDER: S-EPMC5617769 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature