Integrative Biology 200A University of California, Berkeley "PRINCIPLES OF PHYLOGENETICS" Spring 2006 The What the Hell Do I Do with All These Trees Lab We’ve generated a lot of trees in the last few weeks. Today we’re going to explore different ways to view, compare, and manipulate those trees. First we’re going to use TreeView to look at a consensus tree generated in MrBayes. Then we’re going to compare a bunch of trees with the same taxa but different topology using PAUP* and generate several types of consensus trees. Finally we’re going to generate a consensus tree from trees that have overlapping but not identical taxa using Matrix Representation with Parsimony. We’re going to be using many different files for this lab, so I put together a single file on line containing all of them at http://ib.berkeley.edu/courses/ib200a/Tree_Lab/. TreeView TreeView is a solid program for viewing trees and generating printable versions of those trees. This will be very useful to you when you’re doing your projects, as most of the programs that generate trees either don’t print trees at all or make really crappy ones. It is available free on line from http://taxonomy.zoology.gla.ac.uk/rod/treeview.html. -The first thing you need to do is go to the TreeView web site, download the Mac version of the program and install it. -Next download the MrBayes Consensus Cephalopod from the web page I set up. This is a consensus tree generated by MrBayes for the Cephalopod COI dataset we’ve been using. It has two trees in it with identical topology. The first has branch lengths and node support values. The second has only branch lengths. -Open TreeView and open the tree file in it. -Pull down the style menu and change the font size, so that you can easily read the names. -Push the Radial Tree (this button is just a picture that looks like a network) at the top of the page. You will see your tree as a network. -Push the phylogram button and the Internal labels button (both just pictures). The tree should now appear as a square phylogram with branchlengths that can be seen in the lengths of the branches and node support values as numbers. -Use the arrow buttons to view the other tree in the file, which in this case is just the same tree without internal node labels.-Go to the tree menu and select Define Outgroup. Double click Alluroteuthis (this is an arbitrary choice). Now hit OK. -Pull down the Tree menu again and select Root with outgroup. This should reroot the tree in the display with Alluroteuthis in the outgroup. It will look very different but will still have the same topology. -To generate a picture for use in your paper pull down the File menu and select Print Preview. Then click Picture to save that tree as a metafile for use with other programs, or Copy to paste it into another program. Tree Distances Now we’re going to use PAUP* to generate a number of different tree distance measures on a bunch of trees with the same taxa, like we talked about in class. -Download the Cephalopod Matrix and the MrBayes Cephalopod Tprbs from the web site. It contains the first 13 trees from the tprobs file for the cephalopod dataset. This has the highest 50% of trees that I found during stationarity. It also has the estimated posterior probabilities of those trees. -Open PAUP*. -Before you can open a tree file in PAUP* you have to have a data matrix with the same taxa open. So open the matrix file that you downloaded first. Then open the tree file. -Pull down the trees menu and select Tree to tree distances. -For the first run we’ll do symmetric differences. This is just a measure of the partitions that the two trees do not share. A branch can be viewed as a partition, because it separates the taxa into two groups. So if branches in both trees separate the taxa into the same two groups, then that partition is shared. Thus more similar trees will disagree on fewer partitions and so have smaller symmetric differences. -Hit OK. This should output a matrix of pairwise differences between the trees, and a frequency distribution of those differences. Are the trees with higher posterior probabilities more like the tree with the highest posterior probability? (Remember these trees are listed in the order of their posterior probabilities.) Is the tree with the highest posterior probability more similar to the other trees than they are in general to each other? Why would this be? What trees have the biggest differences? -Repeat this analysis, only this time use the Agreement “d”. This is a measure of how many taxa you have to remove to make two trees the same with a correction added on so that if the taxa removed are further apart you get a bigger number. Thus more similar trees should have smaller differences. How do the trees compare under thismeasure of difference? Do the two metrics produce similar histograms? Which metric is more informative? Consensus Trees Now we’re going to generate several different consensus trees from that same tree file using PAUP*. I want to emphasize that this is not the appropriate way to generate a consensus tree from MrBayes. It is much better to use the sumt command in MrBayes, because that will consider the trees based on their estimated posterior probabilities and will also calculate branch lengths. However, there are many other situations when you would want to use this method, such as if you generate several most parsimonious trees. I’m just using this tree file, because it is convenient. -Pull down the Trees menu and select Compute Consensus. -First let’s generate a Strict Consensus. Select it then hit OK. This will output a tree that only contains nodes present in all your input trees. When generating consensus trees, PAUP* will not hold the consensus trees in its tree buffer. If you want to save the consensus trees, you have to select a file to save them to in the Compute Consensus window by clicking Output to tree file. There is no need to do that right now, but it may be important for you in the future. -Now let’s generate a Majority Rule tree with a cut off at 50%. This will output a tree with all the nodes that appear in more than 50% of the tree. It will also tell you in what percentage of those trees the nodes occurred. Does this have the same topology as the strict consensus? Are they compatible? -Generate another Majority Rule tree, only this time up
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