You might be thinking, hey, what a cool resource. But how do I actually use the 10kTrees
website for my research, and what am I supposed to do with so many trees?
First of all, you probably don't need 10,000 trees - honestly, it sounded better to say "10kTrees" than "1kTrees", although there might be some legitimate reasons to use the full 10,000 trees.
Putting that detail aside, it still is hard to know how one would integrate analyses across 1000 trees, or even just 100 trees. You might want to assess how phylogenetic uncertainty affects the results, but how is this actually done? And can you avoid sitting in from of your computer running each analysis 100 (or more) times?
And more generally, how should you make use of this resource in terms of downloading a bunch of trees, viewing them, and modifying them, for example by adding a lineage to a block of trees?
The answers to these questions can be found in the four exercises that follow. The exercises use a single dataset, and they make use of R and other programs. If you are interested in using comparative methods, R is well worth learning. It takes some time, but once you get the hang of it, you will never use another statistics package again! The exercises provided on the 10kTrees
website give a sneak peak into the power and flexibility of R, and they can be used as a "recipe" to follow for your comparative analyses. In most cases, you can simply copy and paste the code into R.
teaches you how to download a set of trees. It focuses on the mechanics of the website itself.
gives details on viewing the trees in four different programs: R, Mesquite, FigTree and DensiTree. We especially recommend using R, as it provides a way to easily automate analyses, and thus will help when it comes to running hundreds of analyses. DensiTree is also useful, as it provides a way to visualize the variation in the trees in your tree block.
shows you how to use R to add a species to every tree in a treeblock. Try doing that 100 times in Mesquite and you'd end up in an asylum! It is a breeze with the code we provide for R.
Finally, Exercise 4
gives examples for calculating independent contrasts or running phylogenetic generalized least squares (PGLS) analysis across a tree block. It also gives details on running BayesTraits, which is well suited for analyses of multiple trees.
We suggest that you work through all four exercises in order. Of course, if you want to skip ahead, we understand... and because the exercises are linked through analysis of a common example, we provide the files that are produced in each exercise so that you can do the later exercises without doing the earlier ones.
Good luck, and as always, let us know if we can clarify or help in any way, including by providing additional exercises.