|Publication Type||Journal Article|
|Year of Publication||2011|
|Authors||de Bakker, PI, Graham, RR, Altshuler, D, Henderson, BE, Haiman, CA|
|Journal||Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|
Genetic association studies can be made more cost-effective by exploiting linkage disequilibrium patterns between nearby single-nucleotide polymorphisms (SNPs). The International HapMap Project now offers a dense SNP map across the human genome in four population samples. One question is how well tag SNPs chosen from a resource like HapMap can capture common variation in independent disease samples. To address the issue of tag SNP transferability, we genotyped 2,783 SNPs across 61 genes (with a total span of 6 Mb) involved in DNA repair in 466 individuals from multiple populations. We picked tag SNPs in samples with European ancestry from the Centre d'Etude du Polymorphisme Humain, and evaluated coverage of common variation in the other samples. Our comparative analysis shows that common variation in non-African samples can be captured robustly with only marginal loss in terms of the maximum r2. We also evaluated the transferability of specified multi-marker haplotypes as predictors for untyped SNPs, and demonstrate that they provide equivalent coverage compared to single-marker tests (pairwise tags) while requiring fewer SNPs for genotyping. The efficacy of a tagging-based approach in studying genotype-phenotype correlations in complex traits is strongly supported by our empirical results.