Successfully merging genotype data for different individuals requires complete overlap in SNPs. SNPs that are missing by design (due to different genotyping platforms) from some studies will be correlated with the primary phenotype for that dataset. This might cause spurious results in any secondary analysis on related traits. Although a missing SNP can be imputed, it will have a higher degree of inaccuracy in imputed compared with genotyped SNPs, potentially creating differential measurement error that could also lead to bias [41,46,47]. Therefore, we first looked at the overlap of SNPs between different genotyping arrays and identified three broad platform families with high degree of overlap within category but low overlap across categories–the earlier generation of Illumina arrays (HumanHap), the Illumina OmniExpress array and Affymetrix 6.0 array. The HumanHap platform had a total of 459,999 SNPs compared with 565,810 SNPs for OmniExpress and 668,283 SNPs for Affymetrix 6.0. However, the intersection among all three platform families was only 75,285 SNPs (Fig 1). To achieve the largest GWAS datasets as possible without losing SNP information, we created three datasets–HumanHap comprising six GWAS
