Thomas Duncan C, Haile Robert W, Duggan David
Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089-9011, USA.
Am J Hum Genet. 2005 Sep;77(3):337-45. doi: 10.1086/432962. Epub 2005 Aug 1.
With the imminent availability of ultra-high-volume genotyping platforms (on the order of 100,000-1,000,000 genotypes per sample) at a manageable cost, there is growing interest in the possibility of conducting genomewide association studies for a variety of diseases but, so far, little consensus on methods to design and analyze them. In April 2005, an international group of >100 investigators convened at the University of Southern California over the course of 2 days to compare notes on planned or ongoing studies and to debate alternative technologies, study designs, and statistical methods. This report summarizes these discussions in the context of the relevant literature. A broad consensus emerged that the time was now ripe for launching such studies, and several common themes were identified--most notably the considerable efficiency gains of multistage sampling design, specifically those made by testing only a portion of the subjects with a high-density genomewide technology, followed by testing additional subjects and/or additional SNPs at regions identified by this initial scan.
随着超高通量基因分型平台即将以可承受的成本问世（每个样本可检测100,000 - 1,000,000个基因型），人们对于针对多种疾病开展全基因组关联研究的可能性兴趣日增，但迄今为止，在设计和分析此类研究的方法上几乎没有达成共识。2005年4月，一个由100多名研究人员组成的国际小组在南加州大学举行为期两天的会议，就计划中或正在进行的研究交流经验，并对替代技术、研究设计和统计方法展开讨论。本报告结合相关文献总结了这些讨论内容。会上形成了广泛共识，即开展此类研究的时机已经成熟，还确定了几个共同主题，其中最显著的是多阶段抽样设计能大幅提高效率，特别是仅用高密度全基因组技术检测一部分受试者，然后对初次扫描确定区域的其他受试者和/或其他单核苷酸多态性（SNP）进行检测所带来的效率提升。
