Skol Andrew D, Scott Laura J, Abecasis Gonçalo R, Boehnke Michael
Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
Genet Epidemiol. 2007 Nov;31(7):776-88. doi: 10.1002/gepi.20240.
Genome-wide association (GWA) studies require genotyping hundreds of thousands of markers on thousands of subjects, and are expensive at current genotyping costs. To conserve resources, many GWA studies are adopting a staged design in which a proportion of the available samples are genotyped on all markers in stage 1, and a proportion of these markers are genotyped on the remaining samples in stage 2. We describe a strategy for designing cost-effective two-stage GWA studies. Our strategy preserves much of the power of the corresponding one-stage design and minimizes the genotyping cost of the study while allowing for differences in per genotyping cost between stages 1 and 2. We show that the ratio of stage 2 to stage 1 per genotype cost can strongly influence both the optimal design and the genotyping cost of the study. Increasing the stage 2 per genotype cost shifts more of the genotyping and study cost to stage 1, and increases the cost of the study. This higher cost can be partially mitigated by adopting a design with reduced power while preserving the false positive rate or by increasing the false positive rate while preserving power. For example, reducing the power preserved in the two-stage design from 99 to 95% that of the one-stage design decreases the two-stage study cost by approximately 15%. Alternatively, the same cost savings can be had by relaxing the false positive rate by 2.5-fold, for example from 1/300,000 to 2.5/300,000, while retaining the same power.
全基因组关联（GWA）研究需要对数千名受试者的数十万个标记进行基因分型，按照当前的基因分型成本来说费用高昂。为了节省资源，许多GWA研究采用分阶段设计，即第一阶段对一部分可用样本进行所有标记的基因分型，第二阶段对剩余样本进行这些标记中的一部分的基因分型。我们描述了一种设计具有成本效益的两阶段GWA研究的策略。我们的策略保留了相应单阶段设计的大部分效能，同时将研究的基因分型成本降至最低，同时考虑到第一阶段和第二阶段基因分型成本的差异。我们表明，第二阶段与第一阶段每个基因型成本的比率会强烈影响研究的最优设计和基因分型成本。增加第二阶段每个基因型的成本会将更多的基因分型和研究成本转移到第一阶段，并增加研究成本。通过采用在保持假阳性率的同时降低效能的设计，或者在保持效能的同时提高假阳性率，可以部分缓解这种较高的成本。例如，将两阶段设计中保留的效能从单阶段设计的99%降低到95%，可使两阶段研究成本降低约15%。或者，通过将假阳性率放宽2.5倍，例如从1/300,000放宽到2.5/300,000，同时保持相同的效能，也可以实现相同的成本节省。
