PAUP
PAUP (Phylogentic analysis using parsimony…and other methods) is one of the most highly
used phylogenetic software programs. The new version does distance, parsimony and maximum
likelihood methods. This sheet will give you an a rough idea of how to use the program, but a
little knowledge can be dangerous. If you don’t understand what you are doing, ask someone in
the lab who does.
We often use PAUP in conjunction with MODELTEST, a program that evaluates the best
molecular model of evolution for your data
1. Open your file in PAUP and select Edit.
2. Next, OPEN then file PAUP4 Modelblock, and hit EDIT.
3. Highlight and copy the text of this file and paste THE ENTIRE TEXT at the very bottom
of your file file.
4. Save the file under a new file name.
5. Under FILE, select OPEN, select this new file, and EXECUTE. A screen should come up
with a bunch of text that will change frequently. It may take 5-10 minutes (or longer) to
complete. You will know when it’s done because it will say “processing of file
completed”.
6. When run is complete, a file called MODEL.SCORES will be created in the same folder
that the original file was in.
7. Close PAUP
8. Open MODELTEST
9. Click INPUT FROM FILE and specify the MODEL.SCORES file that was just created.
10. Click OUTPUT TO FILE and specify a name and location for the file.
11. The program will run in a fraction of a second and the output file will be created.
12. In PAUP, open your file and the output file that you created from ModelTest. The later
will have a block of likelihood scores and a list of hierarchical of likelihood ratio test
results. At the base of this file is “Model Selected is:” This is your best model and is
followed by all of the model parameters that best fit your data.
13. COPY the model block from “[!Likelihood settings…” to “end;” (be sure to include [ ]
and ;)
14. PASTE the modelblock to the very bottom of your original PAUP file (the one without
the modelblock), then save.
15. EXECUTE your file in PAUP.
16. In DATA, go to DEFINE OUTGROUP. Select the sequences from your outgroup. Often
you can get outgroup senquences from Genbank.
17. In OPTIONS, go to ROOTING
18. Select MAKE INGROUP MONOPHYLETIC, hit OK
DISTANCE METHODS
19. Under ANALYSIS, go to DISTANCE
20. Next under ANALYSIS, go to DISTANCE SETTINGS
21. Under DNA/RNA distances, select the distance metric that you’d like to use.
22. In ANALYSIS, go to NEIGHBORJOINING/UPGMA. Select Neighborjoining and hit
OK.
23. Under TREES, go to TREE SCORES. Select Distance and write down the tree score.
24. In TREES, go to PRINT NJ TREE
25. In PLOT TYPE, Select PHYLOGRAM
26. Hit PREVIEW
27. Save tree as PICT file. Also, print the tree.
PARSIMONY ANALYSIS
28. Next, in ANALYSIS, change to PARSIMONY
29. In ANALYSIS go to HEURISTIC SEARCH
30. Press SEARCH
31. If there is more than one most parsimonious tree, in TREES, go to COMPUTE
CONSENSUS.
32. Select STRICT
33. In TREES select PRINT CONSENSUS
34. In PLOT TYPE, Select PHYLOGRAM
35. Hit PREVIEW
36. Save tree as PICT file. Also, print the tree.
LIKELIHOOD ANALYSIS
37. In ANALYSIS, change optimality criterion to LIKELIHOOD.
38. In ANALYSIS go to LIKELIHOOD SETTINGS.
39. In ANALYSIS, go to HEURISTIC SEARCH.
40. The model parameters of your data should be entered automatically if you put the PAUP
block in appropriately from ModelTest.
41. Hit SEARCH. This may take a very long time, be prepared to wait.
42. Again, print the tree and save it as a pict file, as done before. Like parsimony there may
be multiple trees and you may need to compute a consensus.
BOOTSTRAPPING
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EXECUTE your data file
Define your outgroup, as done before.
Set optimality criterion to PARSIMONY
Under ANALYSIS, go to BOOTSTRAP/JACKKNIFE
Select BOOTSTRAP, and set it for 100 Replicates. Retain all groups will
Frequencies greater than 60%.
Hit Continue and Search
When finished, in TREES, go to PRINT BOOTSTRAP CONSENSUS
Select Rectangular Cladogram. Select Show Group Frequencies
Print the bootstrap consensus tree
KISHINO HASEGAWA TEST
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In MacClade, open your data file.
In DISPLAY, go to GO TO TREE WINDOW
Select DISPLAY RANDOM BUSH
Dragging individual branches, create two groups of sequences for each population
(hypothesis: populations are monophyletic groups)
5. In the TOOLS menu, find the collapse clade tool and collapse each population clade into
monophyletic polytomies, one for each population
6. In TREE menu, go to STORE TREE and save as MONOPHYLY CONTRAINT
7. Save the MacClade file
8. Under TREE save tree file as Monophyly constraint. Close file
9. Open Allsilversides in PAUP and EXECUTE
10. Define your outgroup
11. Set optimality criterion to PARSIMONY
12. In ANALYSIS, go to LOAD CONSTRAINT
13. Open MONOPHYLY CONTRAINT
14. In ANAYLSIS, go to HEURISTIC SEARCH
15. In GENERAL SEARCH OPTIONS, click ENFORCE TOPOLOGICAL
CONSTRAINTS, keeping trees that ARE COMPATIBLE with constraints
16. Hit SEARCH
17. Save tree to file HK TEST
18. In ANAYLSIS, go to HEURISTIC SEARCH
19. In GENERAL SEARCH OPTIONS, unclick ENFORCE TOPOLOGICAL
CONSTRAINTS, so that the heuristic search will no longer enforce the constraint tree.
20. Hit SEARCH
21. Save trees to the same file HK TEST. When asked, say APPEND FILE. You should now
have three trees in the HK TEST treefile
22. Open the HK TEST treefile
23. Rather than adding all the trees together in one tree block, APPENDING the tree file
merges two independent files together. You must now edit the file to create a single tree
block. First, label the tree(s) that you got with the monophyly constraint so that you know
what is what. Then, copy one tree block (e.g. “tree PAUP_1 = …..) into the other so that
there is only one treeblock
24. In TREES go to GET TREES FROM FILE
25. Open HK TEST treefile and press GET TREES. Multiple trees should be imported into
PAUP.
26. Go to TREES, TREES SCORES, and click LIKELIHOOD
27. Click TOPOLOGY TESTS
28. Click Kishino-Hasegawa Test, Normal distribution, and one-tailed and hit OK