运用基因型统计量对数量性状位点进行关联分析

随着基因分型技术的不断发展，遗传学家可以获得大量遗传标记的基因型和单体型数据，这为鉴定人类复杂疾病基因提供了前所未有的机会。当不能直接获得单体型数据时，可以使用基因型数据的统计方法来进行关联分析．使用基因型数据对疾病基因进行关联分析的统计方法可以扩充到定位数量性状位点（QTL）。本文扩充了对疾病基因进行关联分析的主成份分析统计量PG咒和熵统计量％。到数量性状，利用选择基因型对QTL进行关联分析。计算机模拟考察了两个统计量的I型错误率．基于10个遗传性血色病（Hereditaryhaemochromatosis）单体型频率的计算机模拟调查了两个统计量的统计功效．结果表明两个统计量PCTt和TGE可以有效地对QTL进行关联分析．

The Application of the Genotype- based Statistics for Association Analysis of QTL

With the advent of large - scale genotyping technologies, the availability of enormous quantities of geno- type or haplotype data provides an unprecedented opportunity for identifying genes underlying complex traits. When haplotypes are not directly observed, genotype - based statistical approaches can be used in association analysis. Genotype - based statistical methods for association study of complex disease may be directly adopted and/or extended to quantitative -trait locus （QTL） mapping for quantitative traits. In this paper, we extended the adaptive principal component test （APRICOT） PCTL and the entropy - based statistic TeE for mapping complex disease gene to quantita- tive trait for association analysis of QTL through the method of selective genotyping. The type I error rates are exam- ined under the null hypothesis of no association by simulation. The power was investigated by simulation on the base of haplotype frequencies of 10 SNPs of angiotensin - I converting enzyme （ACE） genes. The results show that the two statistics PCTL and TGE are valid and have high power for genomic association study of QTL.