Abstract
Background: Supertrees combine disparate, partially overlapping trees to generate a synthesis that provides a high level perspective that cannot be attained from the inspection of individual phylogenies. Supertrees can be seen as meta-analytical tools that can be used to make inferences based on results of previous scientific studies. Their meta-analytical application has increased in popularity since it was realised that the power of statistical tests for the study of evolutionary trends critically depends on the use of taxon-dense phylogenies. Further to that, supertrees have found applications in phylogenomics where they are used to combine gene trees and recover species phylogenies based on genome-scale data sets.Results: Here, we present the L.U.St package, a python tool for approximate maximum likelihood supertree inference and illustrate its application using a genomic data set for the placental mammals. L.U.St allows the calculation of the approximate likelihood of a supertree, given a set of input trees, performs heuristic searches to look for the supertree of highest likelihood, and performs statistical tests of two or more supertrees. To this end, L.U.St implements a winning sites test allowing ranking of a collection of a-priori selected hypotheses, given as a collection of input supertree topologies. It also outputs a file of input-tree-wise likelihood scores that can be used as input to CONSEL for calculation of standard tests of two trees (e.g. Kishino-Hasegawa, Shimidoara-Hasegawa and Approximately Unbiased tests).Conclusion: This is the first fully parametric implementation of a supertree method, it has clearly understood properties, and provides several advantages over currently available supertree approaches. It is easy to implement and works on any platform that has python installed.Availability: bitBucket page - https://[email protected]/afro-juju/l.u.st.git.Contact: [email protected].
Original language | English |
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Article number | 183 |
Pages (from-to) | 1-6 |
Journal | BMC Bioinformatics |
Volume | 15 |
Issue number | 1 |
DOIs | |
Publication status | Published - 12 Jun 2014 |
Keywords
- Maximum likelihood
- Phylogenomics
- Supertrees
- Tests of two trees
ASJC Scopus subject areas
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Applied Mathematics
- Structural Biology