Multipoint linkage mapping using sibpairs: non-parametric estimation of trait effects with quantitative covariates.
Multipoint linkage mapping using sibpairs: non-parametric estimation of trait effects with quantitative covariates.
复制标题
使用同胞对的多点连锁图：具有定量协变量的性状效应的非参数估计。
DOI：
10.1002/gepi.20036
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Chiu,Yen-Feng
中科院分区：
文献类型：
--
作者：
Chiou,Jeng-Min;Liang,Kung-Yee;Chiu,Yen-Feng
使用同胞对设计的多点连锁分析仍然是一种常用的方法，以帮助研究人员缩小染色体区域的性状（定性或定量）的兴趣。尽管这种方法很受欢迎，但它的成功在很大程度上取决于如何正确处理遗传异质性、基因-基因和基因-环境相互作用等问题。如果处理得当，检测遗传连锁和有效估计性状位点位置的可能性将得到提高，有时会大幅提高。以前，我们已经提出了一种方法来处理这些问题，通过建模的目标性状基因座的遗传效应作为一个函数的协变量有关的sibpairs。在这里，遗传效应仅仅是一对同胞在性状位点上与他们的父母共享相同等位基因的概率。这种建模有助于将同胞对划分为更同质的亚组，这反过来又有助于提高检测连锁的机会。这种方法的一个局限性是需要对协变量进行分类，以便引入少量和固定数量的遗传效应参数。在这份报告中，我们利用的事实是，现在多个标记是容易获得的基因分型同时进行。这表明可以非参数化地估计类属效应对协变量的依赖性。我们提出了一个迭代过程来估计（1）非参数的遗传效应和（2）性状位点的位置，通过估计功能梁等。（《希伯来书》51：67-76）。我们将这种新的方法应用于精神分裂症的连锁研究，以说明每个同胞对的发病年龄可能有助于解决遗传异质性的问题。这一分析揭示了新的光的性状效应的发病年龄从受影响的sibpairs的依赖性，以前没有发现的观察。此外，我们还进行了一些模拟工作，表明该方法为估计数量性状基因座的位置提供了准确的推断。Genet.流行病学© 2004 Wiley-Liss，Inc.
Multipoint linkage analysis using sibpair designs remains a common approach to help investigators to narrow chromosomal regions for traits (either qualitative or quantitative) of interest. Despite its popularity, the success of this approach depends heavily on how issues such as genetic heterogeneity, gene-gene, and gene-environment interactions are properly handled. If addressed properly, the likelihood of detecting genetic linkage and of efficiently estimating the location of the trait locus would be enhanced, sometimes drastically. Previously, we have proposed an approach to deal with these issues by modeling the genetic effect of the target trait locus as a function of covariates pertained to the sibpairs. Here the genetic effect is simply the probability that a sibpair shares the same allele at the trait locus from their parents. Such modeling helps to divide the sibpairs into more homogeneous subgroups, which in turn helps to enhance the chance to detect linkage. One limitation of this approach is the need to categorize the covariates so that a small and fixed number of genetic effect parameters are introduced. In this report, we take advantage of the fact that nowadays multiple markers are readily available for genotyping simultaneously. This suggests that one could estimate the dependence of the generic effect on the covariates nonparametrically. We present an iterative procedure to estimate (1) the genetic effect nonparametrically and (2) the location of the trait locus through estimating functions developed by Liang et al.([2001a] Hum Hered 51: 67–76). We apply this new method to the linkage study of schizophrenia to illustrate how the onset ages of each sibpair may help to address the issue of genetic heterogeneity. This analysis sheds new light on the dependence of the trait effect on onset ages from affected sibpairs, an observation not revealed previously. In addition, we have carried out some simulation work, which suggests that this method provides accurate inference for estimating the location of quantitative trait loci. Genet. Epidemiol.© 2004 Wiley-Liss, Inc.