Improving bayesian population dynamics inference: A coalescent-based model for multiple loci

Molecular Biology and Evolution

Volumn 30, Issue 3, 2013, Pages 713-724

  Gill, Mandev S ^a   Lemey, Philippe ^b   Faria, Nuno R ^b   Rambaut, Andrew ^c   Shapiro, Beth ^d   Suchard, Marc A ^a,e  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b REGA INSTITUTE FOR MEDICAL RESEARCH   (Belgium)

^c UNIVERSITY OF EDINBURGH   (United Kingdom)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

coalescent; effective population size; Gaussian Markov random fields; smoothing

Indexed keywords

ARTICLE; BAYES THEOREM; CAMEROON; DNA SEQUENCE; DYNAMICS; EFFECTIVE POPULATION SIZE; GENE LOCUS; GENE SEQUENCE; GENEALOGY; GENETIC VARIABILITY; GROWTH; HUMAN IMMUNODEFICIENCY VIRUS 1; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; HUMAN IMMUNODEFICIENCY VIRUS PREVALENCE; LAST COMMON ANCESTOR; MOLECULAR GENETICS; MONTE CARLO METHOD; MULTILOCUS SEQUENCE TYPING; NONHUMAN; POPULATION DYNAMICS; POPULATION GENETICS; POPULATION SIZE; PROBABILITY; SEQUENCE ALIGNMENT;

ALGORITHMS; BAYES THEOREM; COMPUTER SIMULATION; EVOLUTION, MOLECULAR; GENES, VIRAL; GENETIC LOCI; GENETIC SPECIATION; HIV-1; HUMANS; MARKOV CHAINS; MODELS, GENETIC; MONTE CARLO METHOD; MUTATION; POPULATION DENSITY; POPULATION DYNAMICS; STATISTICS, NONPARAMETRIC;

EID: 84873576867     PISSN: 07374038     EISSN: 15371719     Source Type: Journal    
DOI: 10.1093/molbev/mss265     Document Type: Article

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