The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of a continuous trait, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The POUMM package provides an easy and efficient way to perform this variety of analyses on large macro-evolutionary or epidemic trees. It implements a fast-likelihood calculation algorithm enabling MCMC-sampling with millions of iterations within minutes on contemporary multiple core processors. The package provides functions for configuring the fit of the model and a number of standard generic functions such as logLik, plot, summary, allowing a visual and a statistical assessment of the goodness of fit. This is an important step before using the model fit to answer relevant biological questions.

# Using the R-package

Here is a quick example on how to use the package on a simulated tree and trait data:

# number of tips
N <- 500

# phylogeny
tr <- ape::rtree(N)

# for the example, simulate trait values on the tree according to a POUMM model.
z <- rVNodesGivenTreePOUMM(
tree = tr,
z0 = 0,      # fixed value at the root
alpha = 2,   # selection strength of the OU process
theta = 3,   # long term mean of the OU process
sigma = 1,   # unit-time standard deviation of the OU process
sigmae = 1   # standard deviation of the non-heritable component
)[1:N]         # only the values at the N tips will be available in reality

# A combined ML and MCMC fit of the model with default parameter settings.
fit <- POUMM(z, tr)

plot(fit)
summary(fit)
AIC(fit)
BIC(fit)
coef(fit)
logLik(fit)
fitted(fit)
plot(resid(fit))
abline(h=0)

# fit PMM to the same data and do a likelihood ratio test
fitPMM <- POUMM(z, tr)
lmtest::lrtest(fitPMM, fit)

For an introduction to the model parameters and the package, read the User guide. More advanced topics, such as parametrizations and interpretations of the model fit are covered in the other package vignettes and in the package help-pages, e.g. ?POUMM, ?specifyPOUMM, ?summary.POUMM, ?plot.POUMM.

# Installing the R-package

Read the section Installing the POUMM R-package in Get started.

# Package source-code

The package source-code is available on github.

# Package web-page

Check-out the package web-page for the latest news and further documentation.