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A unified sampling approach for multipoint analysis of qualitative and quantitative traits in sib pairs.

机译:用于同胞对定性和定量性状多点分析的统一采样方法。

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摘要

Recent advances in molecular biology have enhanced the opportunity to conduct multipoint mapping for complex diseases. Concurrently, one sees a growing interest in the use of quantitative traits in linkage studies. Here, we present a multipoint sib-pair approach to locate the map position (tau) of a trait locus that controls the observed phenotype (qualitative or quantitative), along with a measure of statistical uncertainty. This method builds on a parametric representation for the expected identical-by-descent statistic at an arbitrary locus, conditional on an event reflecting the sampling scheme, such as affected sib pairs, for qualitative traits, or extreme discordant (ED) sib pairs, for quantitative traits. Our results suggest that the variance about tau&d4;, the estimator of tau, can be reduced by as much as 60%-70% by reducing the length of intervals between markers by one half. For quantitative traits, we examine the precision gain (measured by the variance reduction in tau&d4;) by genotyping extremely concordant (EC) sib pairs and including them along with ED sib pairs in the statistical analysis. The precision gain depends heavily on the residual correlation of the quantitative trait for sib pairs but considerably less on the allele frequency and exact genetic mechanism. Since complex traits involve multiple loci and, hence, the residual correlation cannot be ignored, our finding strongly suggests that one should incorporate EC sib pairs along with ED sib pairs, in both design and analysis. Finally, we empirically establish a simple linear relationship between the magnitude of precision gain and the ratio of the number of ED pairs to the number of EC pairs. This relationship allows investigators to address issues of cost effectiveness that are due to the need for phenotyping and genotyping subjects.
机译:分子生物学的最新进展增加了对复杂疾病进行多点定位的机会。同时,人们发现对连锁研究中使用定量性状的兴趣日益浓厚。在这里,我们提出了一种多点同胞对方法来定位控制观察表型(定性或定量)的性状基因座的图谱位置(tau)以及统计不确定性。此方法建立在任意位点上的预期逐次下降统计量的参数表示形式上,条件是反映采样方案的事件,例如受影响的同胞对的定性特征或极端不和谐(ED)的同胞对,数量性状。我们的结果表明,通过将标记之间的间隔时间缩短一半,可以将tau的估计量tau&d4;的方差减少60%-70%。对于数量性状,我们通过对极端一致的(EC)同胞对进行基因分型并在统计分析中将它们与ED同胞对一起进行检查,来检查精度增益(通过tau&d4;的方差减少来衡量)。精度增益在很大程度上取决于同胞对的数量性状的残留相关性,而在很大程度上取决于等位基因频率和确切的遗传机制。由于复杂的性状涉及多个基因座,因此残留相关性不容忽视,我们的发现强烈建议人们在设计和分析中都应将EC同胞对与ED同胞对结合在一起。最后,我们凭经验在精度增益的大小与ED对数量与EC对数量之比之间建立简单的线性关系。这种关系使研究人员能够解决由于表型和基因分型受试者的需求而产生的成本效益问题。

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