| Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci. | |
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MedLine Citation:
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PMID: 23180580 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02 AG gene sequences sampled from Cameroon. Our results are consistent with HIV prevalence data and uncover some aspects of the population history that go undetected in Bayesian parametric estimation. Finally, we recover an older and more reconcilable TMRCA for a classic ancient DNA data set. |
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Authors:
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Mandev S Gill; Philippe Lemey; Nuno R Faria; Andrew Rambaut; Beth Shapiro; Marc A Suchard |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-11-22 |
Journal Detail:
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Title: Molecular biology and evolution Volume: - ISSN: 1537-1719 ISO Abbreviation: Mol. Biol. Evol. Publication Date: 2012 Nov |
Date Detail:
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Created Date: 2012-11-27 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8501455 Medline TA: Mol Biol Evol Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, United States. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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