sra - Selection Response Analysis
Artificial selection through selective breeding is an
efficient way to induce changes in traits of interest in
experimental populations. This package (sra) provides a set of
tools to analyse artificial-selection response datasets. The
data typically feature for several generations the average
value of a trait in a population, the variance of the trait,
the population size and the average value of the parents that
were chosen to breed. Sra implements two families of models
aiming at describing the dynamics of the genetic architecture
of the trait during the selection response. The first family
relies on purely descriptive (phenomenological) models, based
on an autoregressive framework. The second family provides
different mechanistic models, accounting e.g. for inbreeding,
mutations, genetic and environmental canalization, or
epistasis. The parameters underlying the dynamics of the time
series are estimated by maximum likelihood. The sra package
thus provides (i) a wrapper for the R functions mle() and
optim() aiming at fitting in a convenient way a predetermined
set of models, and (ii) some functions to plot and analyze the
output of the models.
