Next generation sequencing technologies have made it possible to investigate the role of rare variants (RVs) in disease etiology. Because RVs associated with disease susceptibility tend to be enriched in families with affected individuals, study designs based on affected sib pairs (ASP) can be more powerful than case-control studies. We construct tests of RV-set association in ASPs for single genomic regions as well as for multiple regions. Single-region tests can efficiently detect a gene region harboring susceptibility variants, while multiple-region extensions are meant to capture signals dispersed across a biological pathway, potentially as a result of locus heterogeneity. Within ascertained ASPs, the test statistics contrast the frequencies of duplicate rare alleles (usually appearing on a shared haplotype) against frequencies of a single rare allele copy (appearing on a nonshared haplotype); we call these allelic parity tests. Incorporation of minor allele frequency estimates from reference populations can markedly improve test efficiency. Under various genetic penetrance models, application of the tests in simulated ASP data sets demonstrates good type I error properties as well as power gains over approaches that regress ASP rare allele counts on sharing state, especially in small samples. We discuss robustness of the allelic parity methods to the presence of genetic linkage, misspecification of reference population allele frequencies, sequencing error and de novo mutations, and population stratification. As proof of principle, we apply single- and multiple-region tests in a motivating study data set consisting of whole exome sequencing of sisters ascertained with early onset breast cancer.

中文翻译：

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基于基因和基于途径的检测同胞对中稀有变异的关联。

下一代测序技术使研究罕见变异（RVs）在疾病病因学中的作用成为可能。由于与疾病易感性相关的RVs倾向于在患病个体的家庭中丰富，因此，基于患病同胞对（ASP）的研究设计比病例对照研究更有效。我们针对单个基因组区域以及多个区域构建ASP中RV集关联的测试。单区域测试可以有效地检测出具有易感性变异的基因区域，而多区域扩展则是为了捕获可能由于基因座异质性而分散在整个生物途径中的信号。在确定的ASP中，测试统计数据将重复的罕见等位基因（通常出现在共享单倍型上）的频率与单个罕见等位基因拷贝（出现在非共享单倍型上）的频率进行对比；我们称这些等位基因奇偶检验。从参考人群中纳入次要等位基因频率估计值可以显着提高测试效率。在各种遗传渗透模型下，这些测试在模拟ASP数据集中的应用证明了良好的I型错误特性以及通过回归ASP稀有等位基因计数共享状态的方法获得的功率增益，尤其是在小样本中。我们讨论了等位基因奇偶校验方法对存在遗传连锁，参考群体等位基因频率的错误指定，测序错误和从头突变以及群体分层的鲁棒性。作为原理证明，