GAWMerge expands GWAS sample size and diversity by combining array-based genotyping and whole-genome sequencing.

View Abstract

Genome-wide association studies (GWAS) have made impactful discoveries for complex diseases, often by amassing very large sample sizes. Yet, GWAS of many diseases remain underpowered, especially for non-European ancestries. One cost-effective approach to increase sample size is to combine existing cohorts, which may have limited sample size or be case-only, with public controls, but this approach is limited by the need for a large overlap in variants across genotyping arrays and the scarcity of non-European controls. We developed and validated a protocol, Genotyping Array-WGS Merge (GAWMerge), for combining genotypes from arrays and whole-genome sequencing, ensuring complete variant overlap, and allowing for diverse samples like Trans-Omics for Precision Medicine to be used. Our protocol involves phasing, imputation, and filtering. We illustrated its ability to control technology driven artifacts and type-I error, as well as recover known disease-associated signals across technologies, independent datasets, and ancestries in smoking-related cohorts. GAWMerge enables genetic studies to leverage existing cohorts to validly increase sample size and enhance discovery for understudied traits and ancestries.

Investigators
Abbreviation
Commun Biol
Publication Date
2022-08-11
Volume
5
Issue
1
Page Numbers
806
Pubmed ID
35953715
Medium
Electronic
Full Title
GAWMerge expands GWAS sample size and diversity by combining array-based genotyping and whole-genome sequencing.
Authors
Mathur R, Fang F, Gaddis N, Hancock DB, Cho MH, Hokanson JE, Bierut LJ, Lutz SM, Young K, Smith AV, , Silverman EK, Page GP, Johnson EO