Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (λ ∼ 1.8–2.0). Relative risks as low as λ ∼ 1.1–1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%–35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data.
Advances in high-throughput genotyping technology and the International HapMap Project have enabled genetic association studies at the whole-genome level. Our paper describes two genome-wide SNP panels that contain tag SNPs derived from the International HapMap Project. Tag SNPs are proxies for groups of highly correlated SNPs. Information can be captured for the entire group of correlated SNPs by genotyping only one representative SNP, the tag SNP. These whole-genome SNP panels also contain additional content thought to be overrepresented in disease, such as amino acid–changing nonsynonymous SNPs and mitochondrial SNPs. We show that these panels cover the genome with very high efficiency as measured by coverage of all HapMap SNPs and a set of SNPs derived from completely resequenced genes from the Seattle SNPs database. We also show that these panels have high power to detect disease risk alleles for both HapMap and non-HapMap SNPs. In complex disease where multiple risk alleles are believed to be involved, we show that the ability to detect at least one risk allele with the tag SNP panels is also high.