Fast algorithms for computing phylogenetic divergence time

Background The inference of species divergence time is a key step in most phylogenetic studies. Methods have been available for the last ten years to perform the inference, but the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. Fo...

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Veröffentlicht in:BMC bioinformatics Jg. 18; H. Suppl 15; S. 514 - 13
Hauptverfasser: Crosby, Ralph W., Williams, Tiffani L.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 06.12.2017
BioMed Central Ltd
BMC
Schlagworte:
Algorithms
Animals
Bioinformatics
Biomedical and Life Sciences
Computational Biology - methods
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Divergence time
Life Sciences
MCMC
Microarrays
Phylogenetics
Phylogeny
Primates - classification
Primates - genetics
Sequence Analysis, DNA - methods
Software
Time Factors
Phylogenetics
MCMC
Divergence time
ISSN:1471-2105, 1471-2105
Online-Zugang:Volltext
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Zusammenfassung:Background The inference of species divergence time is a key step in most phylogenetic studies. Methods have been available for the last ten years to perform the inference, but the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. For example a study of 349 primate taxa was estimated to require over 9 months of processing time. In this work, we present a new algorithm, AncestralAge, that significantly improves the performance of the divergence time process. Results As part of AncestralAge, we demonstrate a new method for the computation of phylogenetic likelihood and our experiments show a 90% improvement in likelihood computation time on the aforementioned dataset of 349 primates taxa with over 60,000 DNA base pairs. Additionally, we show that our new method for the computation of the Bayesian prior on node ages reduces the running time for this computation on the 349 taxa dataset by 99%. Conclusion Through the use of these new algorithms we open up the ability to perform divergence time inference on large phylogenetic studies.
Bibliographie:ObjectType-Article-1
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-017-1916-1