Determining Inheritance Distributions via Stochastic Penetrances
通过随机外显率确定遗传分布AI 解读 ↓
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通过随机外显率确定遗传分布
- 研究问题
- 在疾病基因定位的连锁分析中，如何刻画给定表型后的遗传向量分布，并据此为不同家系和表型选择得分函数？
- 方法与思路
- 作者将未知始祖等位基因视为隐变量，引入随机外显率因子，并利用相关随机变量的矩与矩母函数构造半参数得分方法。
- 材料陈述的贡献
- 摘要称方法统一处理多种表型及任意家系，并揭示不同阶矩、遗传效应强弱与同祖同源共享之间的得分函数联系。
- 阅读关注点
- 应核对随机外显率因子的定义、得分函数构造条件，以及近交、非加性和非近交情形下不同共享结构的具体作用。
- 阅读边界
- 仅据版本未注明的 OpenAlex 索引摘要；摘要未给出具体模型条件、证明或检验性能，不能推断刊本变化及软件实现细节。
原文摘要
The aim of linkage analysis is to map the position of a gene contributing to an inheritable disease. The statistical model contains the disease allele frequency and penetrance parameters. Here I investigate the inheritance distribution, that is, the conditional distribution of the inheritance vector given phenotypes at the disease locus. Based on this, the likelihood and likelihood score function of Whittemore can be defined. As a result, a general semiparametric methodology of choosing score functions in linkage analysis is proposed. The proposed approach is valid for arbitrary pedigrees, and I treat quantitative, dichotomous (binary), and other phenotypes in a unified framework. The resulting score functions can be easily incorporated into existing software for multipoint linkage analysis. I use the fact that the inheritance distribution depend on unknown founder alleles. These are treated as hidden data and give rise to “stochastic penetrance factors.” Certain uncorrelated unit variance random variables that are functions of the founder alleles are introduced. I show that the moment-generating function and moments of these play crucial roles in choosing likelihoods and likelihood score functions. Lower-/higher-order moments are more important when the genetic effect is weak/strong, and this corresponds to simultaneous identical by descent (IBD) sharing of few/many individuals. For inbred pedigrees and nonadditive models, the likelihood score function is dominated by individuals homozygous by descent at the disease locus. For outbred pedigrees, the local score function involves pairwise IBD sharing. Relations to existing score functions of nonparametric linkage (Spairs, Sall, Srobdom) and quantitative trait loci (QTL) are highlighted.