两位点疾病模型的快速参数求解算法

Fast Parameters Solution Algorithm of Two-point Disease Model

生成模拟数据对全基因组关联分析(GWAS)算法进行测试时,要求按单位点边缘效应大小计算出疾病模型的相关参数,而目前缺乏对应的公开算法。为此,基于二分搜索提出一个数值算法,根据单位点边缘效应和人群疾病发病率计算出3个典型的两位点疾病模型的控制参数。实验结果表明,该算法能快速精确地进行疾病模型参数求解,便于对GWAS算法进行大规模模拟测试。

Generating simulation data to test algorithms of Genome Wide Association Study（GWAS） usually requires calculating parameters of disease models according to single locus marginal effect sizes,but there are no published methods for the calculation.This paper proposes a numerical algorithm to compute parameters of disease models based on binary search.Given the population prevalence and the single locus marginal effect size,the algorithm can calculate the parameters of three typical two-point disease models.Experimental results show that the algorithm is fast and accurate,and it makes extensive simulation tests of GWAS algorithms easier.