Home

Eric W. Goolsby edited this page May 11, 2016 · 8 revisions

Rphylopars is an R package for conducting phylogenetic comparative analyses on multivariate datasets, which may contain multiple intraspecific observations and missing data. Rphylopars uses a linear-time algorithm for fast computations on large datasets, and may be used to perform ancestral state reconstruction, impute missing data, and fit a variety of evolutionary models, including Brownian motion, estimation of tree transformation parameters (Early-Burst, Ornstein-Uhlenbeck, lambda, kappa, delta), and multivariate Ornstein-Uhlenbeck. The following tutorial explores the functionality of Rphylopars using simulated datasets. First, an introduction to simulating data with missing observations and fitting a simple Brownian motion model is provided, with details on missing data imputation, ancestral state reconstruction, and construction of 95% confidence intervals for estimated ancestral or imputed trait values. Next, examples for estimating models such as Pagel's lambda, Ornstein-Uhlenbeck, Early-Burst, and multivariate Ornstein-Uhlenbeck are provided. Finally, methods for handling within-species (phenotypic) variation are discussed.

Refer to the sidebar on the right side of this page for information on specific topics, or proceed to Example 1: Getting Started.

Getting Rphylopars

Rphylopars is available on CRAN and is also under continuous development. To get the most recent version of Rphylopars, download from the Rphylopars GitHub. First, install the devtools package if don't have it already:

install.packages("devtools")

then install Rphylopars from GitHub:

require(devtools)
install_github("ericgoolsby/Rphylopars",dependencies = TRUE)

if the above code doesn't work, run the following:

library(RCurl)
library(httr)
set_config( config( ssl_verifypeer = 0L ) )
install_github("ericgoolsby/Rphylopars",dependencies = TRUE)