Refined Buneman Trees

4.4 Hybrid methods
All the methods we have described until now are very one-sided in their bias,
exploring only one side of the trade-off between accuracy and speed. Hybrid
methods do exist, where a combination of a fast method and an accurate one
might produce a practical method with sound biological meaning.
Another method called Disc Covering is described in [HNP + 98], using a
divide-and-conquer type of approach. From the abstract:
(The Disc-Covering Method) DCM obtains a decomposition of the
input dataset into small overlapping sets of closely related taxa,
reconstructs trees on these subsets (using a “base” phylogenetic
method of choice), and then combines the subtrees into one tree on
the entire set of taxa. Because the subproblems analyzed by DCM
are smaller, computationally expensive methods such as maximum
likelihood estimation can be used without incurring too much cost.
4.5 Accuracy of inferred trees
It is possible to evaluate the quality or confidence of branches in the evolutionary
trees we find using our tree reconstruction methods. These statistical methods
are known as bootstrap tests, and they are described [NK00], with references to
other articles.
The basic idea is to find some tree T using some method M, forsomedata
set D. Lets say D consists of n nucleotide sequences. Now we may select n
sequences from D with replacement, to form a new sample dataset D ′ —notice
that the same sequence might occur several times in the new set, while some
sequences might not occur at all. Now we use the new sample to infer a new tree
T ′ bythesamemethodM, andbycomparingT and T ′ we can assign a count
of1tothebranchesinT which also occur in T ′ , and 0 to the rest. Repeating
this process many times (e.g a thousand times) yields a statistic of how often
each branch occurs for different samples, and thus a reflection of how confident
we can be in this particular branch.
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