Variance Component Models for Mapping QTLs

用于绘制 QTL 的方差分量模型

• 批准号: 6803095
• 负责人: JOHN K. HEWITT
• 金额: $ 31.59万
• 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/6803095
• 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（由申请人提供）：人类基因组知识的惊人进步，以及标记技术的平行进步，已经超过了复杂性状统计遗传学方法的互补发展。针对这种情况，目前的建议寻求支持我们的工作，数量性状基因座（QTL）定位，以适应数据结构和模型，是现代遗传研究的设计和分析的实际重要性。我们修改后的更新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），人类遗传学威康信托中心（牛津大学）和统计遗传学中心（密歇根大学）的合作努力。我们的目标是继续这种富有成效的合作是进一步扩展方差分量分析的方法，以适应更一般的数据结构和模型，是现代遗传研究的设计和分析的实际重要性，并将这些集成到一个全面的软件包。具体而言，我们将：1）进一步开发用于所选样品的连锁和关联分析的方法，所述方法不仅是稳健的和无偏的，而且对于应用于一般谱系是足够有效的; 2）使用用于检测这些交互作用效应的最佳选择程序来开发上位性和基因-环境（GE）交互作用的模型; 3）将Fulker等（1999）的模型从单基因座等位基因关联扩展到多基因座单倍型关联，该模型将基因型效应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）通过使用回归来改进多点IBD计算的方法。（Fulker等，1995），以联合收割机组合从我们的软件包MERLIN获得的精确的单标记IBD信息;以及6）将MERLIN扩展为综合方差分量分析包，用于对多变量离散和连续数据进行组合的多点连锁和关联分析，用于选择的和随机的样本。