Identifying predictors of time-inhomogeneous viral evolutionary processes.

ABSTRACT: Various factors determine the rate at which mutations are generated and fixed in viral genomes. Viral evolutionary rates may vary over the course of a single persistent infection and can reflect changes in replication rates and selective dynamics. Dedicated statistical inference approaches are required to understand how the complex interplay of these processes shapes the genetic diversity and divergence in viral populations. Although evolutionary models accommodating a high degree of complexity can now be formalized, adequately informing these models by potentially sparse data, and assessing the association of the resulting estimates with external predictors, remains a major challenge. In this article, we present a novel Bayesian evolutionary inference method, which integrates multiple pot

SUBMITTER: Bielejec F 

PROVIDER: S-EPMC5072463 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature