General Quantitative Genetic Methods for Comparative Biology

  • Pierre de Villemereuil
  • Shinichi Nakagawa


There is much in common between the aim and tools of the quantitative geneticist and the comparative biologist. One of the most interesting statistical tools of the quantitative genetics (QG) is the mixed model framework, especially the so-called animal model, which can be used for comparative analyses. In this chapter, we describe the phylogenetic generalised linear mixed model (PGLMM), which encompasses phylogenetic (linear) mixed model (PMM). The widely used phylogenetic generalised least square (PGLS) can be seen as a special case of PGLMM. Thus, we demonstrate how PGLMM can be a useful extension of PGLS, hence a useful tool for the comparative biologist. In particular, we show how the PGLMM can tackle issues such as (1) intraspecific variance inference, (2) phylogenetic meta-analysis, (3) non-Gaussian traits analysis, and (4) missing values and data augmentation. Further possible extensions of the PGLMM and applications to phylogenetic comparative (PC) analysis are discussed at the end of the chapter. We provide working examples, using the R package MCMCglmm, in the online practical material (OPM).



We are grateful for S. Lavergne, M. Lagisz, L. Z. Garamszegi and two anonymous reviewers for their comments on our earlier versions of this chapter; their comments have significantly improved this chapter. S.N. is supported by the Rutherford Discovery Fellowship (New Zealand).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Laboratoire d’Écologie Alpine (LECA-UMR CNRS 5553)Université Joseph FourierGrenobleFrance
  2. 2.Department of ZoologyUniversity of OtagoDunedinNew Zealand

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