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Expanding the pool of public controls for GWAS via a method for combining genotypes from arrays and sequencing

Mathur, R.; Fang, F.; Gaddis, N.; Hancock, D. B.; Cho, M. H.; Hokanson, J. E.; Bierut, L. J.; Lutz, S. M.; Young, K.; Smith, A. V.; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, ; Silverman, E. K.; Page, G. P.; Johnson, E. O.

2021-10-20 bioinformatics
10.1101/2021.10.19.464854 bioRxiv
Show 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 case-only cohorts 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 type I error and 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.

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