湖南大学学报（自然科学版）2016，Vol.43Issue(10)：155-160,6.
一种分析全基因组上位性的新方法∗
A Genome-wide Epistasis Analysis Method Based on Multiple Criteria Fusion
摘要
Abstract
Traditional units of genome-wide association studies have serious defects such as low repeat-ability,difficulty to interpret,and epistasis analysis based on machine learning has troubles such as high computational complexity and insufficient prediction accuracy.This paper presented a new approach for the analysis of genome-wide epistatic.This method uses the framework of two-phase epistatic analysis meth-od.It includes a filtering stage and an epistatic combinatorial optimization stage.The characteristics of the filtering stage presents a multicriteria fusion strategy for the evaluation of genetic loci from multiple per-spectives to ensure that the weak effect of susceptibility loci can be retained,and then,this method uses the multiple criteria sorting fusion strategy to eliminate the low degree of genetic variation associated with disease states.Epistatic combinatorial optimization phase uses the greedy algorithm combination of heuris-tic search space in order to reduce the time complexity.Finally,a support vector machine was used as the epistatic evaluation model.Experiments with different parameters of linkage disequilibrium SNPruler with classical algorithms were compared with the performance of the ACO,and the experiment results show that the method can effectively keep weak effect locus and improve disease forecasting accuracy considera-bly.关键词
全基因组关联研究/上位性/复杂疾病/智能计算Key words
GWAS (Genome-Wide Association Study)/epistasis/complex diseases/intelligent computing分类
信息技术与安全科学引用本文复制引用
李泽军,陈敏,曾利军..一种分析全基因组上位性的新方法∗[J].湖南大学学报（自然科学版）,2016,43(10):155-160,6.基金项目
国家自然科学基金资助项目(61672223),National Natural Science Foundation of China(61672223) （61672223）
湖南省自然科学基金资助项目(2016JJ4029) （2016JJ4029）
