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上位性模型中方差成分的限制。

Restrictions on components of variance for epistatic models.

作者信息

Tiwari H K, Elston R C

机构信息

Department of Epidemiology and Biostatistics, Rammelkamp Center for Education and Research, Case Western Reserve University, Cleveland, Ohio.

出版信息

Theor Popul Biol. 1998 Oct;54(2):161-74. doi: 10.1006/tpbi.1997.1373.

Abstract

If a disease is caused by several loci, then the additive variance at each locus may represent only small portions of the total genetic variance, while epistatic variance components may explain a significant amount of the total genetic variance. In this paper we first give simple general formulations to derive all the components of total genetic variance in a random sample for any multilocus model. We then derive these components for a series of fifteen models that have been proposed as being the two-allele two-locus models most likely for disease. We discuss the restrictions and limitations on the penetrance and the gene frequencies, implied by the disease prevalence, for each model. We investigate the relative magnitudes of the components of variance for the various models and show that in six of the models one or other of the epistatic variance components can be larger than each of the other components. It is suggested that investigations be undertaken to develop appropriate sampling and analytical techniques to detect these variance components by linkage analysis.

摘要

如果一种疾病由多个基因座引起,那么每个基因座的加性方差可能仅占总遗传方差的一小部分,而上位性方差成分可能解释了相当一部分总遗传方差。在本文中,我们首先给出简单的通用公式,以推导任意多位点模型随机样本中总遗传方差的所有成分。然后,我们针对一系列已被提出的、被认为最有可能是疾病相关的双等位基因双基因座模型中的15个模型推导这些成分。我们讨论了每个模型中疾病患病率所隐含的对基因外显率和基因频率的限制和局限性。我们研究了各种模型中方差成分的相对大小,并表明在其中六个模型中,一个或另一个上位性方差成分可能大于其他每个成分。建议开展研究以开发适当的抽样和分析技术,通过连锁分析检测这些方差成分。

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