Haplotype analysis of population and pedigree data in association studies

关联研究中群体和谱系数据的单倍型分析

• 批准号: 7409876
• 负责人: Kui Zhang
• 金额: $ 1.5万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-27 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7409876
• 关键词: Academia; Address; Alleles; Area; Attention; Chromosome Mapping; Chromosomes; Communities; Computing Methodologies; Data; Dependency; Development; Disease; Evolution; Funding; Genes; Genetic; Genetic Markers; Genotype; Government; Haplotypes; Human; Individual; Industry; Inherited; Knowledge; Lead; Learning; Link; Linkage Disequilibrium; Localized; Maps; Methods; Numbers; Play; Population Analysis; Research; Research Personnel; Role; Scientist; Single Nucleotide Polymorphism; Societies; Variant; base; cost effective; design; genetic linkage analysis; genetic pedigree; genome-wide analysis; human disease; insight; interest; novel; symposium

DESCRIPTION (provided by applicant): Association studies either based on genome wide analysis and localized fine mapping through linkage disequilibrium (LD) have become increasingly popular as they represent a potentially more cost effective and powerful approach for gene mapping than linkage analysis. Haplotypes refer to combinations of marker alleles which are located closely together on the same chromosome and which tend to be inherited together. Haplotypes play an important role in association studies because haplotype based approaches may provide additional power for mapping disease genes and also provide insight on the factors influencing the dependencies among genetic markers (i.e., LD). Such insights may provide information essential for understanding human evolution and also for identifying cis-interactions between two or more causal variants. For these reasons, haplotype based methods have drawn much attention and have long been of great interest of genetic societies. However, despite the rapid progress on this research area, haplotype analysis using a large number of tightly linked single nucleotide polymorphisms (SNPs) is just being developed and poses great challenges to scientists because the genotype other than the haplotypes of each individual is generated in large scale studies. In addition, it is still unclear how best to perform the haplotype analysis and to what extent and in what context the haplotype analysis can increase power for association studies. Therefore, a focused meeting on relevant methodological and applied issues on haplotype analysis can stimulate novel ideas and exchange different views/approaches that can lead to more powerful and efficient analyses of haplotypes. To address this need, we request funds to support a conference on haplotype analysis of population and pedigree data in association studies in which leading researchers on haplotype analysis convene to discuss the best use of haplotypes to identify genes underlying common human diseases. The specific aims of this conference are to review the up-to-date methodological development of haplotype analysis, to explore novel statistical and computational methods designed for haplotype analysis, to discuss strategies for the best use of haplotypes, and to disseminate the knowledge and lessons learned from this conference to the general scientific community. The meeting will take place in December of 2007 and be attended by scientists from academia, government, and industry.

描述（由申请人提供）： 基于全基因组分析和通过连锁不平衡（LD）进行的局部精细定位的关联研究已经变得越来越流行，因为它们代表了比连锁分析潜在的更经济有效和强大的基因定位方法。单倍型是指在同一染色体上紧密定位在一起并且倾向于一起遗传的标记等位基因的组合。单倍型在关联研究中起着重要作用，因为基于单倍型的方法可以为绘制疾病基因提供额外的力量，并且还提供对影响遗传标记之间依赖性的因素的了解（即，LD）。这种见解可能提供必要的信息，了解人类进化，也为确定两个或两个以上的因果变异之间的顺式相互作用。由于这些原因，基于单倍型的方法引起了广泛的关注，并且长期以来一直受到遗传学会的极大兴趣。然而，尽管在这一研究领域取得了快速进展，但使用大量紧密连锁的单核苷酸多态性（SNP）的单倍型分析才刚刚发展，这给科学家带来了巨大的挑战，因为每个个体的单倍型以外的基因型是在大规模研究中产生的。此外，目前还不清楚如何最好地进行单倍型分析，在何种程度上和在何种情况下，单倍型分析可以增加关联研究的权力。因此，关于单倍型分析的相关方法和应用问题的集中会议可以激发新的想法并交流不同的观点/方法，从而导致更强大和更有效的单倍型分析。为了满足这一需求，我们要求资金支持一个关于关联研究中人口和谱系数据的单倍型分析的会议，在该会议上，单倍型分析的主要研究人员聚集在一起，讨论单倍型的最佳使用，以确定常见人类疾病的基因。本次会议的具体目标是回顾最新的单倍型分析方法的发展，探索新的统计和计算方法设计的单倍型分析，讨论策略，最好地利用单倍型，并传播知识和经验教训，从这次会议到一般的科学界。会议将于2007年12月举行，来自学术界、政府和工业界的科学家将出席会议。