In summary, we present GAWMerge, a protocol for integrating array and WGS genotype data to conduct GWAS with a case-only and public control design. This protocol overcomes previous obstacles to using public controls13. The ability to use WGS data for public controls (1) ensures complete overlap with variants on any array used for genotyping of cases, and (2) provides a much larger pool of public controls to draw from, especially for non-Europeans, from ancestrally diverse resources like TOPMed. In our proof-of-concept study, we applied GAWMerge to WGS data from TOPMed (specifically, COPDGene and ECLIPSE cohorts) as public controls for array-genotyped case datasets. We first showed that the two genotyping technologies are compatible by comparing array- and WGS-derived genotypes for the same samples from COPDGene and demonstrating a lack of false positives. We then showed that GAWMerge controls type-I error, as evidenced by the expected lack of genome-wide significant findings in a GWAS meta-analysis comparing smoker cases vs. smoker controls from independent datasets. Lastly, GAWMerge recovered known COPD-associated findings from Hobbs et al28. including CHRNA3 on chromosome 15, FAM13A on chromosome
