BMC Bioinformatics [electronic resource]
Algorithms; Humans; Phylogeny; Software
BACKGROUND: Recent advances in sequencing technology have created large data sets upon which phylogenetic inference can be performed. Current research is limited by the prohibitive time necessary to perform tree search on a reasonable number of individuals. This research develops new phylogenetic algorithms that can operate on tens of thousands of species in a reasonable amount of time through several innovative search techniques.
RESULTS: When compared to popular phylogenetic search algorithms, better trees are found much more quickly for large data sets. These algorithms are incorporated in the PSODA application available at http://dna.cs.byu.edu/psoda
CONCLUSIONS: The use of Partial Tree Mixing in a partition based tree space allows the algorithm to quickly converge on near optimal tree regions. These regions can then be searched in a methodical way to determine the overall optimal phylogenetic solution.
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Sundberg, K., Clement, M., Snell, Q., Ventura, D., Whiting, M., & Crandall, K. (2012). Phylogenetic search through partial tree mixing.. BMC Bioinformatics [electronic resource], 13 (suppl. S8). http://dx.doi.org/10.1186/1471-2105-13-S13-S8