数量性状遗传关联分析中的统计方法研究

项目名称： 数量性状遗传关联分析中的统计方法研究

项目编号： No.11301465

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 数理科学和化学

项目作者： 潘东东

作者单位： 云南大学

项目金额： 22万元

中文摘要： 随着现代生物技术的进步，以人类全基因组数据为研究对象的关联性检验方法已成为识别复杂疾病遗传基因和致病机理的一种有效方法。该类方法主要以基因组上数以万计的单核苷酸多态性(SNP)为出发点来研究复杂疾病与潜在的危险因素之间的关系。针对病例-对照设计下0-1型性状数据已有许多成熟的统计分析方法，相较之下，数量性状的关联分析更具挑战性，对其统计方法的研究正处于不断进展中，并逐渐成为遗传关联研究领域的热门方向之一。本项目侧重研究连续型性状的定量数据与SNP变异之间的关联，考虑遗传模型不确定性因素，提出新的具有稳健性质的检验统计量；给出一种基于改进的F统计量的两阶段设计方案及相应的P-值计算方法；针对稀有变异，提出适用该类型数据的稳健统计检验方法；研究多个SNP之间的交互作用对复杂疾病的影响，给出相比已有方法具有功效优势的检验统计量；通过模拟研究和实际数据分析的结果验证所提新方法的可行性和准确性。

中文关键词： 全基因组关联研究；数量性状；稳健统计检验；遗传模型不确定性；

英文摘要： With the progress of modern biotechnology, the statistical association test for whole genome data has become an effective method to identify the genetic and pathogenic mechanism underlying many complex human diseases. Taking the tens of thousands of single nucleotide polymorphisms (SNPs) in the genome as the starting point, the study aim is to investigate the relationship between complex disease and potential risk factors. There have been numerous mature approaches for analyzing 0-1 type trait or disease data under the case-control design. Meanwhile, quantitative trait association studies gradually become a hot topic but more challenging. In this project, we focus on the study of the association between quantitative traits and SNPs, taking the genetic model uncertainty into account, propose novel testing statistics with robust properties. Additionally, we will give a robust two stage design scheme and the corresponding calculation method for the statistical significance (p-value) based on the modified F-statistic. For the data of rare variants, we will provide a robust statistical method to test the association between rare variants and quantitative traits. Moreover, we will discuss the influence of the interaction of multiple SNPs on complex diseases, and give more efficient testing statistics for new data type

英文关键词： GWAS；Quantitative traits；Robust statistical test；Genetic model uncertainty；