Abstract

Phylogenetically based statistical methods are now standard in comparative biology, and the best understood methods are phylogenetically independent contrasts, Monte Carlo simulations, and generalized least squares (GLS) models. Free software is widely available only for independent contrasts, but has limited application of the latter two methods. Therefore, using the freely available, multi-platform, and open-source R statistical language, we have written a set of functions (the R package PHYLOGR) to implement phylogenetic Monte Carlo and GLS methods. These programs provide easy reading, manipulation, and plotting of simulated data sets, as well as functions to fit statistical models to those simulated data sets (including linear models of any complexity; principal components analysis; canonical correlation analysis; generalized least squares). We present several examples that use PHYLOGR, including the analysis of phylogenetically simulated data with principal components and with various linear models. Other examples demonstrate the fitting of GLS models with a variance-covariance matrix derived from a phylogenetic tree. Because R provides a coherent environment for graphics and data analysis, and it is fairly easy to program, the R environment will simplify extensions of the current package to accommodate future developments in the analysis of phylogenetically structured data.