Li Qing, Schwender Holger, Louis Thomas A, Fallin M Daniele, Ruczinski Ingo
Statistical Genetics Section, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA.
Hum Hered. 2013;75(1):12-22. doi: 10.1159/000348789. Epub 2013 Mar 27.
Statistical approaches to evaluate interactions between single nucleotide polymorphisms (SNPs) and SNP-environment interactions are of great importance in genetic association studies, as susceptibility to complex disease might be related to the interaction of multiple SNPs and/or environmental factors. With these methods under active development, algorithms to simulate genomic data sets are needed to ensure proper type I error control of newly proposed methods and to compare power with existing methods. In this paper we propose an efficient method for a haplotype-based simulation of case-parent trios when the disease risk is thought to depend on possibly higher-order epistatic interactions or gene-environment interactions with binary exposures.
在基因关联研究中，评估单核苷酸多态性（SNP）之间的相互作用以及SNP与环境的相互作用的统计方法非常重要，因为复杂疾病的易感性可能与多个SNP和/或环境因素的相互作用有关。随着这些方法的积极发展，需要用于模拟基因组数据集的算法，以确保新提出方法的I型错误控制得当，并与现有方法比较效能。在本文中，我们提出了一种有效的方法，用于在疾病风险被认为取决于可能的高阶上位性相互作用或与二元暴露的基因-环境相互作用时，对病例-亲代三联体进行基于单倍型的模拟。
