TREEMAP offers a range of randomisation tests (some more experimental than others) designed to help evaluate the relationship between host and parasite phylogenies.
Given that the "best" reconstruction requires n cospeciation events, how do we know if this is meaningful or not? One approach is to ask what are the chances of getting n cospeciations by chance alone. TREEMAP allows you to randomise either the host or the parasite tree, or both simultaneously. For each randomised tree (or pair of trees), TREEMAP uses its heuristic algorithm to compute the maximum number of cospeciation events between the two trees.
You can choose to randomise either the host tree, the parasite tree, or both simultaneously. Once you have chosen which option you desire, TREEMAP then displays a dialog box asking you how many random trees you want to generate, under which model they are generated, and how to seed the random number generator.
If you choose User value then TREEMAP uses the value you supply, otherwise TREEMAP takes a seed from your computer's system clock. If you supply a seed it must be in the range 1 to 2,147,483,646. If you use the same seed each time then the same set of random trees will be generated.
The result of the randomisation test is a histogram of the frequency of the maximum number of cospeciation events between the pairs of trees generated. This is displayed in the Histogram window.
If your trees have branch lengths (e.g., amounts of sequence divergence) then you can do one or more simple randomisation tests to assess the significance of the correlation between branch lengths in the host and parasite trees.
Choose the Randomise | Branch lengths command. TREEMAP displays a dialog box similar to the one for random trees:
If you have additive trees, TREEMAP will randomly reassign the observed branch lengths in the parasite tree, then compute the correlation coefficient between the randomised branch lengths and the observed host branch lengths.
Ultrametric trees (molecular clock)
If you have ultrametric host and parasite trees, you can either use a simple Yule model to generate random coalescent times for the parasites, or randomise the
intervals between the observed coalescence times to generate new coalescence times (this will be described in more detail elsewhere).
As with the random trees, the Histogram Window displays the results of the randomisation test.