基于主成分分析下候选基因关联检验的数学模型

对候选基因的关联检验,都是针对性状在候选基因内使用多个SNP标记,并通过检验SNP单倍型来完成的,众所周知,多标记单倍型方法往往要比单标记方法表达出更多的信息,但是,单倍型的数量往往会随着所标记的SNP的数目增多而急剧的增加,这又会大大增加检验统计量的自由度,使用统计学中的主成分分析法来降低单倍型空间的维数,并构造关联检验来检验一个数量性状与多个单倍型的关联情况,模拟结果显示,此检验方法是较合理的.

Mathematical Model of Association Tests for Candidate Genes Based on The Principal Component Analysis

candidate genes association tests are performed by using several intragenic SNPs, simultaneously,by testing SNP haplotype.It is widely recognized that multi-marker haplotypes are more informative than a single marker.But,the number of haplotypes increases with the increase in the number of typed SNPs,As a result,large numbers of haplotypes will introduce large degrees of freedom in haplotype-based tests.In this article,we propose using the principal component method of statistics to reduce the dimension of tests,and then construct association test to test the association between haplotypes and a quantitative trait.Our simulation results show that the proposed test is reasonable.