Abstract
Two extreme types of data may be available for discriminating between alternative modes of inheritance: data on two inbred lines, their F1 and the backcrosses, or data on a sample of relatives drawn from a random mating population. For the former kind of data a ten-parameter model is proposed that subsumes, as special cases, one-locus, two-locus, polygenic, or mixed major locus/polygenic inheritance for a quantitative trait For the latter kind of data three basic models are compared for detecting major gene segregation: the generalized major gene (transmission probability) model, the mixed major gene/polygenic inheritance model and the flexible regressive models. In all cases it is assumed that the environmental variation is normally distributed. The principle of maximizing expected entropy can be used to choose the best-fitting specific genetic hypothesis and, using the general model as a baseline, the likelihood ratio criterion can be used to test for departure from any specific hypothesis. It is recognized that these segregation analysis models can only suggest, never prove, the existence of monogenic segregation.
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© 1990 Springer-Verlag Berlin Heidelberg
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Elston, R.C. (1990). Models for Discrimination Between Alternative Modes of Inheritance. In: Gianola, D., Hammond, K. (eds) Advances in Statistical Methods for Genetic Improvement of Livestock. Advanced Series in Agricultural Sciences, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-74487-7_3
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DOI: https://doi.org/10.1007/978-3-642-74487-7_3
Publisher Name: Springer, Berlin, Heidelberg
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