![]() The third command ("lscore 1 ") tells PAUP* to calculate the likelihood of the tree, in the course of which it will also estimate the shape parameter of the gamma distribution using likelhood. The second command ("lset.") sets the model used for likelihood calculations to be the model used by Mesquite in the simulations, except that the shape parameter used is not specified, but is instead estimated from the data. While this might not be the best way to get a tree, but it will be fast, and give a tree that is good enough for our purposes. The first command ("nj ") will find a neighbor-joining tree. There are equivalent ways to give these commands in the MacOS versions using dialog boxes, but it is much easier for us to describe what to do with these text commands.) (If you don't know how to give PAUP* commands, please read your PAUP* documentation. Lset nst=1 basefreq=equal rates=gamma shape=estimate In PAUP* 4, execute the file Simulated Matrix, and then execute the following commands: Choose (Character Matrix) Characters>Save Copy of Matrix>simulated to save a copy of your newly created matrix perhaps name the file "Simulated Matrix". First, save the matrix to a file so that you can read it into PAUP*. Mesquite will then simulate evolution, and a matrix will be produced, such as this one:Įxamining the results of the simulation Let's see whether the rate variation between characters suggested by this simulated matrix matches a gamma distribution with shape parameter 1.5, as used in the model. When it asks for the name of the matrix to be created, call it "simulated" (although you could choose another name, if you wish). When it queries for the number of character, choose a large number, such as 2000. (There might be other options presented, such as Evolve Continuous Characters, but we don't wish to try that now.) You will then need to chose the model of DNA sequence evolution choose the composite one you created earlier called "full model". As we wish to evolve a DNA sequence up the tree's branches, choose "Evolve DNA characters" from the list. ![]() You will be asked what sort of character simulator to use. This will ask Mesquite to simulate evolution of characters up the current tree in the tree window to produce a new matrix. Simulating evolution Now choose (Tree) Characters>Make New Matrix from>Simulated Matrices on Current Tree. When a button like this is present in a Mesquite window, touching on it will display a small note with information about how to use the window's feature. Note that the dialog box in which you edited "my full model" has button with a ? on it ( ). The model "my full model" is now ready to use. The only element of this model we will change is the character rates model choose "my gamma model" from the drop-down menu to select the gamma distribution model you created as the model of site-to-site rate variation. ![]() If one presumes (as we will) that there were four categories of rates, then this model presumes that one quarter of the characters have rate 0.225, one quarter 0.589, one quarter 1.05, and the rest 2.136, as shown in the following figure: To make it interesting, though, let's presume that some characters evolve more quickly than others, with the distribution of rates of change following a discrete gamma distribution with shape parameter 1.5. One common form of model specifies the relative frequencies of A, C, G, and T the relative rates of change of the different characters and the relative rates of change between A and C, A and G, and so on.įor sake of simplicity, let's presume that A, C, G, and T occur at equal frequencies, and that all pairs of nucleotides have equal rates of change between them.
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