QGglmm-package: Estimate Quantitative Genetics Parameters from Generalised...

In QGglmm: Estimate Quantitative Genetics Parameters from Generalised Linear Mixed Models

Description

Compute various quantitative genetics parameters from a Generalised Linear Mixed Model (GLMM) estimates. Especially, it yields the observed phenotypic mean, phenotypic variance and additive genetic variance.

Details

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This package gives the values on the observed scale for several quantitative genetics parameter using estimates from a Generalised Linear Mixed Model (GLMM). If a fitness function is assumed or measured, it also predicts the evolutionary response to selection on the observed scale.

The two main functions of this package are QGparams and QGpred. The first allows to compute the quantitative genetics parameters on the observed scale for any given GLMM and its estimates. The second allows to compute a predicted response to evolution on the observed scale using GLMM estimates and an assumed/measured/inferred fitness function.

For some distribution/link models (e.g. Binomial/probit and Poisson and Negative Binomial with logartihm or square-root link), a closed form solutions of the integrals computed by this package are available. They are automatially used by QGparams and this function only.

Author(s)

Pierre de Villemereuil <[e-mail]>

Maintainer: Pierre de Villemereuil <[e-mail]>

References

de Villemereuil, P., Schielzeth, H., Nakagawa, S., and Morrissey, M.B. (2016). General methods for evolutionary quantitative genetic inference from generalised mixed models. Genetics 204, 1281-1294.

QGglmm documentation built on Jan. 7, 2020, 5:06 p.m.