A0861
Title: Powerful and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies
Authors: Zilin Li - Northeast Normal University (China) [presenting]
Abstract: Meta-analysis of whole-genome/exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. The aim is to present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze quantitative and dichotomous traits, and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through a meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the trans-omics for precision medicine (TOPMed) program, it is shown that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, several conditionally significant rare variant associations are identified with lipid traits. It is further demonstrated that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.
