Multi-tissue and network models for next-generation EQTL studies

项目摘要 这项研究提案的长期目标是提供一个框架， 工具，以推进分析和理解表达数量性状基因座（eQTL）在单一和 多组织研究，并阐明组织间差异的基因型基础。该提案 分为四个目标：（1）从网络分析中开发统计工具的双向扩展， 可以提高远（反）端eQTL的鉴定;（2）发展新的快速eQTL的统计方法 关联作图，提供可靠的估计效应大小;（3）扩展我们现有的多组织eQTL 将程序导入能够处理20至30个组织的现有数据集的高组织建模平台; （4）建立基于基因的eQTL分析模型。拟议方法的制定将 由最近的大规模eQTL研究驱动，其中研究人员发挥了关键作用。所得 计算工具将解决当前在分析这些新数据集方面的关键缺陷， 对于更广泛的eQTL分析社区具有广泛的实用性。

Project Summary The long-term objective of this research proposal is to provide a framework, and statistical and computational tools, to advance the analysis and understanding of expression quantitative trait loci (eQTL) in single and multi-tissue studies, and to elucidate the genotypic basis of differences between tissues. The proposal is divided into four Aims: (1) to develop bipartite extensions of statistical tools from the analysis of networks that can enhance the identification of distal (trans) eQTLs; (2) to develop new statistical methods for fast eQTL association mapping that provide reliable estimates of effect size; (3) to extend our existing multi-tissue eQTL procedure into a High-Tissue modeling platform capable of handling existing data sets with 20 to 30 tissues; and (4) to develop gene-based statistical models for eQTL analysis. Development of the proposed methods will be driven by recent, large-scale eQTL studies in which the investigators have played key roles. The resulting computational tools will address current, critical shortcomings in the analysis of these new data sets, and will have broad utility for the wider eQTL analysis community.