Variance Component Models for Mapping QTLs

用于绘制 QTL 的方差分量模型

• 批准号: 6547526
• 负责人: JOHN K. HEWITT
• 金额: $ 33.87万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-12-07 至 2007-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6547526
• 关键词: biotechnology; computer data analysis; computer program /software; computer simulation; family genetics; gene environment interaction; gene expression; genetic disorder diagnosis; genetic models; genotype; human data; human population genetics; linkage disequilibriums; linkage mapping; mathematical model; model design /development; phenotype; quantitative trait loci; statistics /biometry

DESCRIPTION (provided by applicant):Spectacular advances in knowledge about the human genome, and parallel advances in marker technology, have out paced the complementary development of methods in statistical genetics for complex traits. In response to this situation, the current proposal seeks support of our work on quantitative trait loci (QTL) mapping to accommodate data structures and models that are of practical importance to the design and analysis of modern genetic studies. Our revised renewal application is to support a collaborative effort from the Institute for Behavioral Genetics (University of Colorado), the Institute of Psychiatry (University of London), the Wellcome Trust Centre of Human Genetics (University of Oxford), and the Center for Statistical Genetics (University of Michigan). Our goal in the continuation of this productive collaboration is to further extend the methodology of variance components analysis to accommodate more general data structures and models that are of practical importance to the design and analysis of modern genetic studies, and to integrate these into a comprehensive software package. Specifically we will: 1) further develop methods for linkage and association analysis of selected samples that are not only robust and unbiased but also sufficiently efficient for application to general pedigrees; 2) develop models for epistasis and gene-environment (GE) interaction using optimal selection procedures for the detection of these interactive effects; 3) extend the Fulker et al (1999) model that partitions genotypic effects into between-sibships and within-sibship components from single locus allelic associations to multilocus haplotype associations; 4) develop variance-components methods that are able to accommodate genotyping errors; 5) refine a method for multipoint IBD calculations by use of regression (Fulker et al, 1995) to combine exact single-marker IBD information obtained from our software package, MERLIN; and 6) extend MERLIN into a comprehensive variance components analysis package for combined, multi-point linkage and association analysis of multivariate discrete and continuous data, for both selected and random samples.

描述(申请人提供)：人类基因组知识的惊人进步，以及标记技术的平行进步，已经超过了复杂特征统计遗传学方法的互补发展。针对这种情况，目前的提案寻求支持我们在数量性状基因座(QTL)定位方面的工作，以适应对现代遗传研究的设计和分析具有实际重要性的数据结构和模型。我们修订后的续签申请是为了支持行为遗传学研究所(科罗拉多大学)、精神病学研究所(伦敦大学)、惠康信托人类遗传学中心(牛津大学)和统计遗传学中心(密歇根大学)的合作努力。我们继续这一富有成效的合作的目标是进一步扩展方差分量分析的方法，以适应对现代遗传研究的设计和分析具有实际重要性的更一般的数据结构和模型，并将它们整合到一个全面的软件包中。具体地说，我们将：1)进一步开发所选样本的连锁和关联分析方法，这些方法不仅稳健和无偏见，而且足够有效地应用于一般家系；2)利用检测这些交互效应的最佳选择程序来开发上位性和基因-环境(GE)交互作用模型；3)扩展Fulker等人(1999)的模型，该模型将遗传效应从单基因座等位基因关联划分为同胞间和同胞内成分；4)开发能够适应基因分型错误的方差分量方法；5)通过使用回归(Fulker et al，1995)改进多点IBD计算方法，以结合从我们的软件包Merlin获得的准确的单标记IBD信息；以及6)将Merlin扩展为一个全面的方差分量分析程序包，用于对选定和随机样本的多变量离散和连续数据进行组合、多点关联和关联分析。