基于网络的全基因组关联分析方法

项目名称： 基于网络的全基因组关联分析方法

项目编号： No.31471246

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 生物科学

项目作者： 邓明华

作者单位： 北京大学

项目金额： 70万元

中文摘要： 认识人类疾病的遗传基础、发现遗传变异导致疾病的生物机制是人类健康的关键。全基因组关联分析(GWAS)旨在检测人群中的复杂性状与基因组上的突变位点之间的关联。表达数量性状(eQTL)分析是将基因表达量作为数量性状，发现可以解释基因表达变化的突变位点，是理解分子机制的重要手段。通常的eQTL分析以单基因、单位点的方式进行，忽略了基因之间、位点之间的可能相互作用，从而造成了统计检验功效的损失。本项目提出基于网络的关联分析方法，从三方面进行研究：其一、网络相关的遗传位点发现，旨在发现影响一组基因之间的调控网络的遗传位点；其二、遗传位点之间上位作用的检测；其三、基于网络的多数据关联分析融合，预测疾病相关的基因.

中文关键词： 表达数量性状；全基因组关联分析；数据整合；网络标记物

英文摘要： Understanding the genetic basis of human disease and the underlying mechanisms of how these diseases are affected by genetic variations is critical for public health.Genome-wide association study (GWAS）aims at detecting variants at genomic loci that are associated with complex traits in the population. Expression quantitative taits loci (eQTL) mapping has been extensively applied to unravel the genetic variants that can explain the variation in gene expression levels， which is important for the identification of disease molecular mechanism. Conventional eQTL mapping generally based on one gene-one marker method, which results in the loss of statistical power. We proposed to study the network based methods, including: (1) Identification of the network associated genetic variants, aiming at the detection of genetic marker which affects the regulatory network among a group of genes; (2) Detection of the epistasis among genetic markers; (3) Network based integration of multiple association studies, to increase the power of detection of disease associate genes.

英文关键词： eQTL;GWAS;Data Integration;Network Biomarker