|Primary Contact(s)||Created||Last Modified||Required Software|
|Rich Glor||1 March 2009||6 March 2011||R|
Comparative biology is a dynamic young field, with new types of analyses and associated software applications appearing constantly. Although this makes for exciting times, it can also make comparative biology a difficult field to learn and master. Making matters worse, most of the available software is relatively user unfriendly and characterized by a variety of alternative user interfaces and idiosyncratic input formats. Over the years, several groups have attempted to bring all of the various phylogenetic comparative analyses into a programming environment. Mesquite is the most popular example of such an effort. Another alternative whose popularity is rapidly expanding is R. Although R lacks the graphical, menu-driven interface of Mesquite it provides users with greater flexibility and more immediate opportunities to develop new applications.
Much like Mesquite, R is not a single program in the traditional sense; it’s better thought of as a framework under which a variety of distinct programs are brought together in a shared working environment. There are tremendous advantages to this approach. For one, it’s relatively easy to write new add-on packages that take advantage of the pre-existing framework. With R, there is no need to write entirely new code to perform functions like tree building or tree plotting. This means that novice programmers can begin using a suite of applications developed by others. A good place to find out about all the phylogenetic comparative analyzes available in R is the task view maintained by Brian O'Meara on the CRAN website http://cran.r-project.org/web/views/Phylogenetics.html.
The goal of the following exercises is to get you familiar with the R environment and its potential applications to comparative studies. Perhaps the greatest draw-back to R is that there can be a relatively steep learning curve for new users. One hurdle is that the R interface is in a command line format, not the type of visually pleasing, pull-down menu driven format that most users prefer. If this is what’s stopping you from learning R the best advice I can give is simply: "get over it." If you want to be on the leading edge of science you need to learn to use command line software. A second problem is that R has a somewhat unusual syntax which will take a bit of getting used to (especially for people who aren’t practiced in computer programming). Stick with it. Everyone ends up banging their head against a wall from time to time when learning a new application: the people who succeed are not smarter than those who fail, they’re just more determined. R is the most powerful computing tool available for practicing comparative biologists and it is worth the effort it will take to learn it.
In the exercises that follow, we will learn (1) how to download and install R and associated packages for phylogenetic analysis, (2) how functions work in R, (3) how trees and associated character data can be uploaded and manipulated in R, and (4) how phylogenetic comparative analyses can be conducted within the R framework.
I. Getting Started with R: Download and install basic phylogenetic applications in R.
II. Tree Basics: Learn how to upload and view phylogenetic trees in R.
III. Loading Character Data into R: Learn how to upload and view phylogenetic trees in R.
IV. Testing Phylogenetic Signal in R: Conduct maximum likelihood-based tests of phylogenetic signal in R.
V. Ancestral Reconstruction with Maximum Likelihood on Discrete Traits in R
VI. Testing Temporal Patterns of Character Evolution in R