Large-Scale Multinomial Inference and Its Applications in Genome-Wide Association Studies

大规模多项式推理及其在全基因组关联研究中的应用

• 批准号: 1007678
• 负责人: Chuanhai Liu
• 金额: $ 23万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1007678&HistoricalAwards=false
• 关键词: Large; Scale; Multinomial; Inference; Its

The investigators study statistical analysis of multinomial counts with alarge number K of categories and a small number n of sample size. This"large K and small n" problem is a very challenging problem that requires thinking about statistical inference at a fundamental level. Employing an auxiliary data-generating approach to reason directly toward probabilistic inference , the PIs develop methods that are probabilistic and have desirable frequency properties. A sequence of topics to be investigated include 1) one-sample and two-sample "large K and small n" multinomial inference; 2) large-scale simultaneous hypothesis testing; 3) application in genome-wide association study; and 4) associated efficient computational methods. The "large K and small n" multinomial inference is motivated by genome-wideassociation studies with a large number of genotypes from singlenucleotide polymorphisms (SNPs) data. SNPs are major genetic variants that mayassociate with common diseases such as cancer and heart disease. With new statistical methods and computing software to be developed in the project, theresearch is expected to generate useful tools for applied statisticians andscientists who are challenged by very-high-dimensional count data.

研究人员研究了具有大量 K 个类别和少量 n 个样本量的多项计数的统计分析。这个“大K小n”问题是一个非常具有挑战性的问题，需要从基础层面思考统计推断。 PI 采用辅助数据生成方法直接进行概率推理，开发出概率性且具有所需频率特性的方法。一系列要研究的主题包括1）单样本和二样本“大K小n”多项式推理； 2）大规模同时假设检验； 3）在全基因组关联研究中的应用； 4) 相关的高效计算方法。 “大 K 和小 n”多项式推断是由全基因组关联研究激发的，其中涉及来自单核苷酸多态性 (SNP) 数据的大量基因型。 SNP 是可能与癌症和心脏病等常见疾病相关的主要遗传变异。随着该项目将开发新的统计方法和计算软件，研究预计将为面临极高维计数数据挑战的应用统计学家和科学家提供有用的工具。