Van Steen Kristel, McQueen Matthew B, Herbert Alan, Raby Benjamin, Lyon Helen, Demeo Dawn L, Murphy Amy, Su Jessica, Datta Soma, Rosenow Carsten, Christman Michael, Silverman Edwin K, Laird Nan M, Weiss Scott T, Lange Christoph
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
Nat Genet. 2005 Jul;37(7):683-91. doi: 10.1038/ng1582. Epub 2005 Jun 5.
The Human Genome Project and its spin-offs are making it increasingly feasible to determine the genetic basis of complex traits using genome-wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome-wide family-based association studies, using single SNPs or haplotypes, can identify associations that achieve genome-wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease-susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease-susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype-tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome-wide significance, as population-based designs do.
人类基因组计划及其衍生项目使得利用全基因组关联研究来确定复杂性状的遗传基础变得越来越可行。分析此类研究的统计挑战源于对数千个单核苷酸多态性（SNP）进行分析时产生的严重多重比较问题。我们用于全基因组基于家系的关联研究的方法，无论是使用单个SNP还是单倍型，都能够识别出达到全基因组显著性的关联。在制定我们筛查工具的指导方针时，我们确定了检测疾病易感位点潜在基因的估计效能下限，该下限不受数据中存在的连锁不平衡结构的影响。我们还评估了在存在多个疾病易感位点的情况下我们方法的效能。我们的筛查工具采用基因组控制并运用单倍型标签SNP的概念。我们的方法使用整个样本，不像基于人群的设计那样需要单独的筛查样本和验证样本才能确立全基因组显著性。
