Estimating genetic architectures from artificial-selection responses: a random-effect framework.

Abstract excerpt

Artificial-selection experiments on plants and animals generate large datasets reporting phenotypic changes in the course of time. The dynamics of the changes reflect the underlying genetic architecture, but only simple statistical tools have so far been available to analyze such time series. This manuscript describes a general statistical framework based on random-effect models aiming at estimating key...

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