基于最小P值方法的罕见变异与数量性状的关联分析

Asociation analysis of rare variants witli quantitative trait based on minimum P-value

全基因组关联分析(GWAS)已经能辨别出许多与复杂疾病相关的常见变异。然而,这些常见变异只能解释疾病遗传力中的一小部分。罕见变异是缺失遗传力的来源之一。本文利用扩展自适应结合P值(ADA)的方法来获得关联检验的P值,能够探测罕见变异与数量性状的关联性,并且能容易的调整协变量。大量的模拟研究表明,当非致病变异的比例比较高、致病变异的影响方向不同时,本方法是稳健的,并且在大多数情况下要比其他几种比较的方法功效高。

Genome-wide association studies(GWAS)can identify a large number of common variants as¬sociated with complex disease.However,they can oly account for a small fraction of disease heritabili-ty.Rare variants are one of sources to contribute to missing heritability.In this paper,we extend an a¬daptive combination of P-values method(termed ADA)to obtain P-values of association tests,which can detect the association of rare variants with a quantitative trait and easily adjust for covariates.Extensive simulation studies indicate that our approach is robust to the inclusion of a high proportion of noncausal variants and the different directions of effects of causal variants,and is more powerful than several other comparison methods in most cases.