Phylodynamic Inference with Kernel ABC and Its Application to HIV Epidemiology.

ABSTRACT: The shapes of phylogenetic trees relating virus populations are determined by the adaptation of viruses within each host, and by the transmission of viruses among hosts. Phylodynamic inference attempts to reverse this flow of information, estimating parameters of these processes from the shape of a virus phylogeny reconstructed from a sample of genetic sequences from the epidemic. A key challenge to phylodynamic inference is quantifying the similarity between two trees in an efficient and comprehensive way. In this study, I demonstrate that a new distance measure, based on a subset tree kernel function from computational linguistics, confers a significant improvement over previous measures of tree shape for classifying trees generated under different epidemiological scenarios. Next, I inco

SUBMITTER: Poon AF 

PROVIDER: S-EPMC4540972 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature