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Improving Divergence Time Estimation in Phylogenetics: More taxa vs. longer sequences
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Mathematical Statistics.
2007 (English)In: Statistical Applications in Genetics and Molecular Biology, ISSN 1544-6115, E-ISSN 1544-6115, Vol. 6, 35- p.Article in journal (Refereed) Published
Abstract [en]

Maximum Likelihood (ML) is used as a standard method for estimating divergence times in phylogenetic trees. The method is consistent and hence the precision can be improved by analyzing longer sequences. In this paper we show that the precision can be improved also by including more taxa to the existing tree. It is a theoretical study, complemented with simulations, showing that the gain in precision is faster with increasing sequence length than with increasing number of taxa. We further compare the results of estimating divergence times using Maximum Likelihood with the much faster and less complex estimation method of Mean Path Length (MPL), which works with the evolution model of Jukes-Cantor (1969). It is shown that MPL is as good as ML in estimating divergence times of nodes that are located near the root in the tree, but ML is better in estimating the divergence times of nodes lower down.

Place, publisher, year, edition, pages
2007. Vol. 6, 35- p.
Keyword [en]
phylogeny, divergence time estimation, maximum likelihood, mean path length
National Category
Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-96723DOI: 10.2202/1544-6115.1313ISI: 000252010600002OAI: oai:DiVA.org:uu-96723DiVA: diva2:171393
Available from: 2008-02-13 Created: 2008-02-13 Last updated: 2017-12-14Bibliographically approved
In thesis
1. On Estimating Topology and Divergence Times in Phylogenetics
Open this publication in new window or tab >>On Estimating Topology and Divergence Times in Phylogenetics
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This PhD thesis consists of an introduction and five papers, dealing with statistical methods in phylogenetics.

A phylogenetic tree describes the evolutionary relationships among species assuming that they share a common ancestor and that evolution takes place in a tree like manner. Our aim is to reconstruct the evolutionary relationships from aligned DNA sequences.

In the first two papers we investigate two measures of confidence for likelihood based methods, bootstrap frequencies with Maximum Likelihood (ML) and Bayesian posterior probabilities. We show that an earlier claimed approximate equivalence between them holds under certain conditions, but not in the current implementations of the two methods.

In the following two papers the divergence times of the internal nodes are considered. The ML estimate of the divergence time of the root is improved if longer sequences are analyzed or if more taxa are added. We show that the gain in precision is faster with longer sequences than with more taxa. We also show that the algorithm of the software package PATHd8 may give biased estimates if the global molecular clock is violated. A change of the algorithm to obtain unbiased estimates is therefore suggested.

The last paper deals with non-informative priors when using the Bayesian approach in phylogenetics. The term is not uniquely defined in the literature. We adopt the idea of data translated likelihoods and derive the so called Jeffreys' prior for branch lengths using Jukes Cantor model of evolution.

Place, publisher, year, edition, pages
Uppsala: Avdelningen för matematisk statistik, 2008. 53 p.
Series
Uppsala Dissertations in Mathematics, ISSN 1401-2049 ; 55
Keyword
Mathematical statistics, Phylogenetics, Divergence Time, Likelihood based methods, Non-informative prior, bootstrap support, Matematisk statistik
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-8441 (URN)978-91-506-1988-1 (ISBN)
Public defence
2008-03-07, Siegbahnsalen, Ångström Laboratory, Lägerhyddsvägen 1, Uppsala, 13:15
Opponent
Supervisors
Available from: 2008-02-13 Created: 2008-02-13 Last updated: 2012-07-26Bibliographically approved

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