Computational and statistical models for human genetics

描述（申请人提供）：在过去的五年中，遗传关联研究以前所未有的详细程度评估了常见SNP变异对复杂性状的贡献。这些全基因组研究不仅依赖于基因分型技术的进步，而且依赖于改进的研究设计以及统计和计算方法的进步-从开发具有成本效益的两阶段设计，到控制群体结构的新策略，再到用于基因型插补和交叉研究荟萃分析的方法和软件。在接下来的五年里，基因分型和测序技术有望再次取得巨大进展。有效地利用这些技术来进一步了解复杂的性状将需要在遗传研究的设计和分析方法方面不断取得进展。在这个应用程序中，我们建立在我们的记录开发实用有用的分析方法，计算工具，并为人类遗传研究的研究设计。我们着手开发计算和统计方法，使人类复杂特征的研究能够有效地利用这些新技术。具体来说，我们将开发新的方法和计算工具，用于基因型插补和短读段序列数据的解释，评估复杂性状研究的基于序列和基因分型的设计策略，并开发统计方法，促进遗传关联研究中可能的功能变体的优先级。!

DESCRIPTION (provided by applicant): In the past five years, genetic association studies have evaluated the contribution of common SNP variation to complex traits at an unprecedented level of detail. These genome wide studies relied not only on advances in genotyping technologies but also on improved study designs and advances in statistical and computational methods - ranging from the development of cost-effective two stage designs, to new strategies to control for population structure, to methods and software for genotype imputation and for cross study meta-analyses. In the next five years, great advances are again expected in genotyping and sequencing technologies. Effectively using these technologies to further our understanding of complex traits will require continued advances in methods for the design and analysis of genetic studies. In this application, we build on our record of developing practical useful analytical methods, computational tools, and study designs for human genetic studies. We set out to develop computational and statistical methods that will enable studies of complex traits in humans to effectively exploit these new technologies. Specifically, we will develop new methods and computational tools for genotype imputation and for the interpretation of short read sequence data, evaluate sequence and genotyping based design strategies for complex trait studies, and develop statistical methods that facilitate the prioritization of likely functional variants in genetic association studies. !