Kruglyak L, Daly M J, Reeve-Daly M P, Lander E S
Whitehead Institute for Biomedical Research, Cambridge.
Am J Hum Genet. 1996 Jun;58(6):1347-63.
In complex disease studies, it is crucial to perform multipoint linkage analysis with many markers and to use robust nonparametric methods that take account of all pedigree information. Currently available methods fall short in both regards. In this paper, we describe how to extract complete multipoint inheritance information from general pedigrees of moderate size. This information is captured in the multipoint inheritance distribution, which provides a framework for a unified approach to both parametric and nonparametric methods of linkage analysis. Specifically, the approach includes the following: (1) Rapid exact computation of multipoint LOD scores involving dozens of highly polymorphic markers, even in the presence of loops and missing data. (2) Non-parametric linkage (NPL) analysis, a powerful new approach to pedigree analysis. We show that NPL is robust to uncertainty about mode of inheritance, is much more powerful than commonly used nonparametric methods, and loses little power relative to parametric linkage analysis. NPL thus appears to be the method of choice for pedigree studies of complex traits. (3) Information-content mapping, which measures the fraction of the total inheritance information extracted by the available marker data and points out the regions in which typing additional markers is most useful. (4) Maximum-likelihood reconstruction of many-marker haplotypes, even in pedigrees with missing data. We have implemented NPL analysis, LOD-score computation, information-content mapping, and haplotype reconstruction in a new computer package, GENEHUNTER. The package allows efficient multipoint analysis of pedigree data to be performed rapidly in a single user-friendly environment.
在复杂疾病研究中,使用多个标记进行多点连锁分析并采用考虑所有系谱信息的稳健非参数方法至关重要。目前可用的方法在这两方面都存在不足。在本文中,我们描述了如何从适度规模的一般系谱中提取完整的多点遗传信息。此信息包含在多点遗传分布中,它为连锁分析的参数法和非参数法提供了统一方法的框架。具体而言,该方法包括以下内容:(1)即使存在环和缺失数据,也能快速精确计算涉及数十个高度多态性标记的多点对数优势分数。(2)非参数连锁(NPL)分析,一种用于系谱分析的强大新方法。我们表明NPL对遗传模式的不确定性具有稳健性,比常用的非参数方法更强大,并且相对于参数连锁分析而言,功效损失很小。因此,NPL似乎是复杂性状系谱研究的首选方法。(3)信息含量映射,它测量可用标记数据提取的总遗传信息的比例,并指出增加标记分型最有用的区域。(4)即使在存在缺失数据的系谱中,也能对多个标记的单倍型进行最大似然重建。我们已在一个新计算机软件包GENEHUNTER中实现了NPL分析、对数优势分数计算、信息含量映射和单倍型重建。该软件包允许在单一用户友好环境中快速高效地对系谱数据进行多点分析。