BioGeography with Bayesian (and likelihood) Evolutionary Analysis with R Scripts
The GitHub repository now contains all updates formerly posted on PhyloWiki. This includes functions for Biogeographical Stochastic Mapping (BSM) and trait-dependent dispersal models. Further updates will be posted to GitHub. Benefit: you will no longer have to use the tedious source() commands that were in the BioGeoBEARS example script.
The R script to run a basic BioGeoBEARS analysis "out of the box" is still posted at PhyloWiki, here: http://phylo.wikidot.com/biogeobears#script .
Other run scripts, and many tips and answers to FAQs, are still available at the various links on the BioGeoBEARS PhyloWiki page: http://phylo.wikidot.com/biogeobears . This material needs to be reorganized, but this will take some time.
To install the GitHub version of BioGeoBEARS, first:
1. Install the new versions of rexpokit and cladoRcpp, both available on CRAN (which gives you binaries for easy installation; the GitHub versions have to be compiled from source):
install.packages("rexpokit")
install.packages("cladoRcpp")
NOTE: If a rexpokit pre-compiled executable is not available on CRAN, this may mean that CRAN took the package down temporarily, and/or required a revision, due to some update of its (constantly changing) FORTRAN standards. I will endeavor to fix these as soon as possible, but I have also archived the previous pre-compiled binaries here:
https://github.com/nmatzke/Matzke_R_binaries
...you will need to match your operating system (e.g. Windows vs. Mac) and perhaps chip type (e.g. x86 Intel vs. amd64; on a Mac, click upper-left Apple Symbol -> About This Mac to get this information).
2. Install the new version of BioGeoBEARS from GitHub, using devtools:
library(devtools)
devtools::install_github(repo="nmatzke/BioGeoBEARS")
Or, if you want to see if byte-compiling leads to a speedup:
library(devtools)
devtools::install_github(repo="nmatzke/BioGeoBEARS", INSTALL_opts="--byte-compile")
If step #2 keeps trying to reinstall rexpokit and cladoRcpp from scratch (including demanding a compiler like gcc or gfortran) even though they are already installed, try adding "dependencies=FALSE":
devtools::install_github(repo="nmatzke/BioGeoBEARS", dependencies=FALSE)
...if you hit other needed dependencies, install them individually from CRAN, then re-run the command above.
3. NOTE: Sometimes, users have extra installations of old versions of R packages. It can take a little work to make sure they are all removed. Instructions for removing old versions:
# library BioGeoBEARS to load whatever you have currently installed
library(BioGeoBEARS)
# Find where this version of package is installed:
find.package(package="BioGeoBEARS")
# You might get something like:
# "/Library/Frameworks/R.framework/Resources/library/"
# Remove and detach the package
remove.packages(pkgs="BioGeoBEARS", lib="/Library/Frameworks/R.framework/Resources/library/")
detach("package:BioGeoBEARS") # (detach might not work or be needed, not sure)
# Repeat until library(BioGeoBEARS) says BioGeoBEARS is not installed:
library(BioGeoBEARS)
find.package(package="BioGeoBEARS")
remove.packages(pkgs="BioGeoBEARS", lib="/Users/nickm/Library/R/3.0/library/")
detach("package:BioGeoBEARS")
library(BioGeoBEARS)
find.package(package="BioGeoBEARS")
remove.packages(pkgs="BioGeoBEARS", lib="/Users/nickm/Library/R/3.1/library/")
detach("package:BioGeoBEARS")
# (Obviously, change the "lib" argument to match
# whatever find.package() returned)
# Once "clean", install BioGeoBEARS from GitHub (see above)
# and make sure you now have the latest version:
library(BioGeoBEARS)
packageVersion("BioGeoBEARS")
# If all the above fails, re-install R and install all packages afresh
# (DON'T install BioGeoBEARS from CRAN, install it from GitHub)
Another discussion of the tools needed to do this are discussed here (or, you can re-install R): https://groups.google.com/forum/#!searchin/biogeobears/detach$20%7Csort:date/biogeobears/2f9etrphhmg/0Jg1YIoOBwAJ
Basically, open R, type library(BioGeoBEARS), and if you already have an install, remove it. Repeat this process until library(BioGeoBEARS) returns an error. THEN install BioGeoBEARS from GitHub.
4. If you get an unexpected error that you didn't used to get, probably you haven't actually updated everything. BE SURE TO CAREFULLY CHECK #1, #2, and #3, above. Use packageVersion to double-check that you've got the correct versions installed:
packageVersion("rexpokit")
# ‘0.26.6.0.9001’ or higher
> packageVersion("cladoRcpp")
# ‘0.15’ or higher
> packageVersion("BioGeoBEARS")
# ‘1.1’ or higher
Next, search the error on the BioGeoBEARS Google Group. If that doesn't help, email the Google Group, and include the specific error messages, and (ideally) the input files and script you were using.
BioGeoBEARS allows probabilistic inference of both historical biogeography (ancestral geographic ranges on a phylogeny) as well as comparison of different models of range evolution. It reproduces the model available in LAGRANGE (Ree and Smith 2008), as well as making available numerous additional models. For example, LAGRANGE as typically run has two free parameters, d (dispersal rate, i.e. the rate of range addition along a phylogenetic branch) and e (extinction rate, really the rate of local range loss along a phylogenetic branch). LAGRANGE also has a fixed cladogenic model which gives equal probability to a number of allowed range inheritance events, e.g.: (1) vicariance, (2) a new species starts in a subset of the ancestral range, (3) the ancestral range is copied to both species; in all cases, at least one species must have a starting range of size 1. LAGRANGE assigns equal probability to each of these events, and zero probability to other events. BioGeoBEARS adds an additional cladogenic event: founder-event speciation (the new species jumps to a range outside of the ancestral range), and also allows the relative weighting of the different sorts of events to be made into free parameters, allowing optimization and standard model choice procedures to pick the best model. The relative probability of different descendent range sizes is also parameterized and thus can also be specified or estimated. The flexibility available in BioGeoBEARS also enables the natural incorporation of (1) imperfect detection of geographic ranges in the tips, and (2) inclusion of fossil geographic range data, when the fossils are tips on the phylogeny. Bayesian analysis has been implemented through use of the "LaplacesDemon" package, however this package is now maintained off of CRAN, so its usage is not formally included in BioGeoBEARS at the current time. CITATION INFO: This package is the result of my Ph.D. research, please cite the package if you use it! Type: citation(package="BioGeoBEARS") to get the citation information.
Current build status (excluding all slow tests): 
BioGeoBEARS version 1.1.1 also includes 156+ unit-tests in the "tests" directory, using the R package "testthat". These check the likelihood calculations, ancestral state probabilities, and ML optimizations for regular, time-stratified, and trait-dependent models.
The tests all run successfully on my Mac, but they take too long to build in Travis-CI (which has a time-limit of 50 minutes). See Build #24 or Build #52 for successful builds that do only some of the tests.
I have also noticed that builds that were working fine suddenly started to fail, due to some change in how Travis-CI's backend handled a C++ Magick library dependency. I wasn't using it but some dependency of some depenency may have needed it. Fixed in Build #70 due to help here.
(The present version of BioGeoBEARS will install from GitHub regardless of the unit-tests issue.)
Matzke, Nicholas J. (2018). BioGeoBEARS: BioGeography with Bayesian (and likelihood) Evolutionary Analysis with R Scripts. version 1.1.1, published on GitHub on November 6, 2018. DOI: http://dx.doi.org/10.5281/zenodo.1478250
Release v1.1.1 registered on Zenodo:
Zenodo link for release: https://zenodo.org/badge/latestdoi/9406671
Zenodo DOI for release: http://dx.doi.org/10.5281/zenodo.1478250