Schneiter Kady, Laird Nan, Corcoran Chris
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
Genet Epidemiol. 2005 Nov;29(3):185-94. doi: 10.1002/gepi.20088.
Family-based study designs have an important role in the search for association between disease phenotypes and genetic markers. Unlike traditional case-control methods, family-based tests use within-family data to avoid identification of spurious associations that may result from population admixture. Many family-based association tests have been proposed to accommodate a variety of ascertainment schemes and patterns of missing data. In this report, we describe exact family-based association tests for biallelic data. Specifically, we discuss test of the null hypotheses "no linkage and no association" and "linkage, but no association". These tests, which are valid under various models for inheritance and patterns of missingness, utilize the procedure proposed by Rabinowitz and Laird [2000: Hum Hered 50:211-223] that provides a unified framework for family based association testing (FBAT). The conditioning approach implemented in FBAT makes an exact test conceptually straightforward, but computationally difficult since the minimum sufficient statistics upon which we condition do not have a conventional form. An exact test may be especially critical when accurate computation of the extreme area of the FBAT statistic is needed, such as when the study design necessitates multiple comparisons adjustments. We describe the exact approach as a useful alternative to the asymptotic test and show that the exact tests for biallelic data may be most useful for the recessive disease model.
基于家系的研究设计在探寻疾病表型与遗传标记之间的关联方面发挥着重要作用。与传统的病例对照方法不同,基于家系的检验使用家系内部的数据,以避免识别可能由群体混合导致的虚假关联。为适应各种确定方案和缺失数据模式,人们提出了许多基于家系的关联检验方法。在本报告中,我们描述了针对二等位基因数据的精确基于家系的关联检验。具体而言,我们讨论了原假设“无连锁且无关联”和“连锁但无关联”的检验。这些检验在各种遗传模型和缺失模式下都是有效的,它们利用了Rabinowitz和Laird [2000: Hum Hered 50:211 - 223]提出的程序,该程序为基于家系的关联检验(FBAT)提供了一个统一的框架。FBAT中实施的条件方法使得精确检验在概念上很直接,但计算起来很困难,因为我们所依据的最小充分统计量没有常规形式。当需要精确计算FBAT统计量的极端区域时,例如当研究设计需要进行多重比较调整时,精确检验可能尤为关键。我们将精确方法描述为渐近检验的一种有用替代方法,并表明针对二等位基因数据的精确检验对于隐性疾病模型可能最为有用。