An evaluation of approaches for rare variant association analyses of binary traits in related samples.

ABSTRACT: Recognizing that family data provide unique advantage of identifying rare risk variants in genetic association studies, many cohorts with related samples have gone through whole genome sequencing in large initiatives such as the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. Analyzing rare variants poses challenges for binary traits in that some genotype categories may have few or no observed events, causing bias and inflation in commonly used methods. Several methods have recently been proposed to better handle rare variants while accounting for family relationship, but their performances have not been thoroughly evaluated together. Here we compare several existing approaches including SAIGE but not limited to related samples using simulations based on the Framingham Heart Stu

SUBMITTER: Chen MH 

PROVIDER: S-EPMC7862354 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature