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针对随机抽样和非随机抽样的数量性状,基于联合协方差和边际的关联与连锁新检验方法。

New joint covariance- and marginal-based tests for association and linkage for quantitative traits for random and non-random sampling.

作者信息

Tiwari Hemant K, Holt Janet, George Varghese, Beasley T Mark, Amos Christopher I, Allison David B

机构信息

Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA.

出版信息

Genet Epidemiol. 2005 Jan;28(1):48-57. doi: 10.1002/gepi.20035.

Abstract

We develop novel statistical tests for transmission disequilibrium testing (tests of linkage in the presence of association) for quantitative traits using parents and offspring. These joint tests utilize information in both the covariance (or more generally, dependency) between genotype and phenotype and the marginal distribution of genotype. Using computer simulation we test the validity (Type I error rate control) and power of the proposed methods, for additive, dominant, and recessive modes of inheritance, locus-specific heritability of the trait 0.05, 0.1, 0.2 with allele frequencies of P=0.2 and 0.4, and sample sizes of 500, 200, and 100 trios. Both random sampling and extreme sampling schemes were investigated. A multinomial logistic joint test provides the highest overall power irrespective of sample size, allele frequency, heritability, and modes of inheritance.

摘要

我们开发了用于定量性状传递不平衡检验(关联存在时的连锁检验)的新型统计检验方法,该检验使用父母和后代的数据。这些联合检验利用了基因型与表型之间协方差(或更一般地,相关性)以及基因型边际分布中的信息。通过计算机模拟,我们针对加性、显性和隐性遗传模式、性状的位点特异性遗传率为0.05、0.1、0.2、等位基因频率为P = 0.2和0.4以及样本量为500、200和100个三联体的情况,检验了所提出方法的有效性(I型错误率控制)和功效。同时研究了随机抽样和极端抽样方案。无论样本量、等位基因频率、遗传率和遗传模式如何,多项逻辑联合检验均具有最高的总体功效。

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