Work

Graph hierarchies for phylogeography

Year: 2013

Type: article

Abstract: Bayesian phylogeographic methods simultaneously integrate geographical and evolutionary modelling, and have demonstrated value in assessing spatial spread patterns of measurably evolving organisms. We improve on existing phylogeographic methods by combining information from multiple phylogeographic datasets in a hierarchical setting. Consider N exchangeable datasets or strata consisting of viral sequences and locations, each evolving along its own phylogenetic tree and according to a conditionally independent geographical process. At the hierarchical level, a random graph summarizes the overall dispersion process by informing which migration rates between sampling locations are likely to be relevant in the strata. This approach provides an efficient and improved framework for analysing inherently hierarchical datasets. We first examine the evolutionary history of multiple serotypes of dengue virus in the Americas to showcase our method. Additionally, we explore an application to intrahost HIV evolution across multiple patients.

Source: Philosophical Transactions of the Royal Society B Biological Sciences

DOI: 10.1098/rstb.2012.0206

Authors: Gabriela B. Cybis, Janet S. Sinsheimer, Philippe Lemey, Marc A. Suchard

Institutions: University of California, Los Angeles, KU Leuven

Language: English

Topic: Genetic diversity and population structure

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Human Genome Research Institute, National Institute of General Medical Sciences

Awards: G4634341335, Statistical Methods for Gene Mapping, Bayesian Joint Estimation of Alignment and Phylogeny, Genomics, EHRs, GPUs, and Next Generation Computational Statistics, Systems in Integrative Biology