Statistical Analysis of RIX for Complex Traits

描述(由申请人提供)： 随着最近对复杂性状的重视重新抬头，新的方法和实验杂交正在开发中。调节大脑生物学和行为的复杂性以及基因环境相互作用的基因尤其难以识别。为了克服这些不足，我们将利用最近描述的重组自交系(Rix)来开发简单而准确的统计方法来定位复杂的数量性状基因座。因此，具体目标是 1)为RIX设计开发适当的统计分析工具； 2)从经验和理论上推导出检验统计量的适当显著阈值； 3)开发实现Rix方法的开源软件。 我们在这个小项目中描述的方法将极大地帮助复杂特征解剖的发展，并应在广泛的研究应用中导致更高的精确度和更准确的致病基因定位，尤其是基因在神经疾病中的作用。

DESCRIPTION (provided by applicant): With the recent resurgence of an emphasis on complex traits, new approaches and experimental crosses are being developed. Genes modulating the complexities of brain biology and behavioral, as well as gene environment interactions have been particularly difficult to identify. In order to overcome some of these deficiencies, we will develop simple yet accurate statistical methods for complex quantitative trait loci mapping using recently described recombinant inbred intercrosses (RIX). Thus the specific aims are to 1) Develop appropriate statistical analysis tools for the RIX design; 2) Derive appropriate significance thresholds of the test statistics empirically and theoretically; and 3) Develop open source software to implement RIX methods. The approaches we describe in this small project will greatly aid developments in complex trait dissection and should lead to greater precision and more accurate localization of the causative genes in a wide variety of research applications, not the least of which is the role of genes in neurological diseases.