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Chunk #14 — Results — Controlling type-I error in case-only vs. public control GWAS

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GAWMerge expands GWAS sample size and diversity by combining array-based genotyping and whole-genome sequencing.
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= 712) vs. WGS from COPDGene AA (N = 1710). All association models include ten principal components as covariates to account for population substructure. COPDGene, COGEND, and ECLIPSE are all smoking cohorts and ratios of COPD were consistent across array and WGS datasets, thus we expected no genome-wide significant association signals (controlled type 1 error). Applying GAWMerge to these data we observed no false positive signals in each separate GWAS analysis (Supplementary Fig. 5) and in their meta-analysis (Fig. 3) results.