  Supertree construction is the process by which a set of phylogenetic trees,
each on a subset of the overall set X of species, is combined into a tree on
the full set S. The traditional use of supertree methods is the assembly of a
large species tree from previously computed smaller species trees; however,
supertree methods are also used to address large-scale tree estimation using
divide-and-conquer (i.e., a dataset is divided into overlapping subsets, trees
are constructed on the subsets, and then combined using the supertree method).
Because most supertree methods are heuristics for NP-hard optimization
problems, the use of supertree estimation on large datasets is challenging,
both in terms of scalability and accuracy. In this paper, we describe the
current state of the art in supertree construction and the use of supertree
methods in divide-and-conquer strategies. Finally, we identify directions where
future research could lead to improved supertree methods.
