|Publication Type||Journal Article|
|Year of Publication||2006|
|Authors||de Bakker, PI, Burtt, NP, Graham, RR, Guiducci, C, Yelensky, R, Drake, JA, Bersaglieri, T, Penney, KL, Butler, J, Young, S, Onofrio, RC, Lyon, HN, Stram, DO, Haiman, CA, Freedman, ML, Zhu, X, Cooper, R, Groop, L, Kolonel, LN, Henderson, BE, Daly, MJ, Hirschhorn, JN, Altshuler, D|
A general question for linkage disequilibrium-based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected dense data uniformly across the four HapMap population samples and eleven other population samples. We picked tag SNPs using genotype data we collected in the HapMap samples and then evaluated the effective coverage of these tags in comparison to the entire set of common variants observed in the other samples. We simulated case-control association studies in the non-HapMap samples under a disease model of modest risk, and we observed little loss in power. These results demonstrate that the HapMap DNA samples can be used to select tags for genome-wide association studies in many samples around the world.