Two-stage designs for gene-disease association studies
Two-stage designs for gene-disease association studies
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DOI：
10.1111/j.0006-341x.2002.00163.x
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发表时间：
2002-03-01
期刊：
影响因子：
1.9
通讯作者：
Begg, CB
中科院分区：
文献类型：
--
作者：
Satagopan, JM;Verbel, DA;Begg, CB
本文的目标是描述一个两阶段设计，当主要设计约束是总成本时，最大限度地提高检测基因疾病关联的能力，总成本由基因评估的总数而不是个体总数表示。在第一阶段中，所有感兴趣的基因在个体的子集上进行评估。然后在第二阶段对其他受试者进行最有希望的基因评估。这将消除在基于第一阶段的结果不太可能与疾病相关的基因上的资源浪费。我们考虑的情况下，基因是相关的，基因是独立的。使用模拟结果，它示出，作为一般的指导方针，当基因是独立的或当相关性是小的，利用75%的资源在第1阶段筛选所有的标记和评估最有前途的10%的标记与剩余的资源提供了接近最佳的功率为广泛的参数配置。这转化为在第1阶段中在约四分之一的所需样本量上筛选所有标志物。
The goal of this article is to describe a two-stage design, that maximizes the power to detect gene disease associations when the principal design constraint is the total cost, represented by the total number of gene evaluations rather than the total number of individuals. In the first stage, all genes of interest arc evaluated on a subset of individuals. The most promising genes are then evaluated on additional subjects in the second stage. This will eliminate wastage of resources on genes unlikely to be associated with disease based on the results of the first stage. We consider the case where the genes are correlated and the case where the; genes are independent. Using simulation results, it is shown that, as a general guideline when the genes arc independent or when the correlation is small, utilizing 75% of the resources in stage 1 to screen all the markers and evaluating the most promising 10% of the markers with the remaining resources provides near-optimal power for a broad range of parametric configurations. This translates to screening all the markers on approximately one quarter of the required sample size in stage 1.