The genetic analysis of age-dependent traits: modeling the character process.
The genetic analysis of age-dependent traits: modeling the character process.
复制标题
作者：
S. Pletcher;C. Geyer
柯克帕特里克及其同事开始将经典数量遗传学扩展到处理功能值特征（也称为无限维特征），例如生长曲线、死亡率曲线和反应规范。在该理论中，单个性状的方差分量的类似物是函数值性状的协方差函数。在这里提出的方法中，我们对协方差函数采用了各种参数模型，这些模型具有许多理想的特性：函数（1）是正定的，（2）可以使用当前用于单个性状的程序进行估计，（3）参数数量较少，（4）允许轻松测试简单的假设。这些方法使用来自一项大型实验的数据进行了说明，该实验检查了自发突变对果蝇特定年龄死亡率的影响。我们的方法比标准的多变量分析效果更好，标准的多变量分析假设每个年龄的性格值都是不同的性格。讨论了将协方差函数建模为一系列正交多项式的现有方法的优点。
The extension of classical quantitative genetics to deal with function-valued characters (also called infinite-dimensional characters) such as growth curves, mortality curves, and reaction norms, was begun by Kirkpatrick and co-workers. In this theory, the analogs of variance components for single traits are covariance functions for function-valued traits. In the approach presented here, we employ a variety of parametric models for covariance functions that have a number of desirable properties: the functions (1) are positive definite, (2) can be estimated using procedures like those currently used for single traits, (3) have a small number of parameters, and (4) allow simple hypotheses to be easily tested. The methods are illustrated using data from a large experiment that examined the effects of spontaneous mutations on age-specific mortality rates in Drosophila melanogaster. Our methods are shown to work better than a standard multivariate analysis, which assumes the character value at each age is a distinct character. Advantages over existing methods that model covariance functions as a series of orthogonal polynomials are discussed.