Sykes Jenna, Cheng Lu, Xu Wei, Tsao Ming-Sound, Liu Geoffrey, Pintilie Melania
Department of Biostatistics, Princess Margaret Hospital, 610 University Avenue, Toronto, ON M5G 2M9, Canada.
BMC Proc. 2011 Nov 29;5 Suppl 9(Suppl 9):S97. doi: 10.1186/1753-6561-5-S9-S97.
The upcoming release of new whole-genome genotyping technologies will shed new light on whether there is an associative effect of previously immeasurable rare variants on incidence of disease. For Genetic Analysis Workshop 17, our team focused on a statistical method to detect associations between gene-based multiple rare variants and disease status. We added a combination of rare SNPs to a common variant shown to have an influence on disease status. This method provides us with an enhanced ability to detect the effect of these rare variants, which, modeled alone, would normally be undetectable. Adjusting for significant clinical parameters, several genes were found to have multiple rare variants that were significantly associated with disease outcome.
即将推出的新型全基因组基因分型技术将为之前无法测量的罕见变异对疾病发病率是否存在关联效应提供新的线索。在遗传分析研讨会17上，我们的团队专注于一种统计方法，以检测基于基因的多个罕见变异与疾病状态之间的关联。我们将罕见单核苷酸多态性（SNP）组合添加到一个已显示对疾病状态有影响的常见变异中。这种方法使我们有更强的能力检测这些罕见变异的效应，而单独建模时这些效应通常是无法检测到的。在对重要临床参数进行校正后，发现有几个基因具有多个与疾病结局显著相关的罕见变异。
