A spatially varying two-sample recombinant coalescent, with applications to HIV escape response

Part of Advances in Neural Information Processing Systems 21 (NIPS 2008)

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Alexander Braunstein, Zhi Wei, Shane Jensen, Jon Mcauliffe


Statistical evolutionary models provide an important mechanism for describing and understanding the escape response of a viral population under a particular therapy. We present a new hierarchical model that incorporates spatially varying mutation and recombination rates at the nucleotide level. It also maintains sep- arate parameters for treatment and control groups, which allows us to estimate treatment effects explicitly. We use the model to investigate the sequence evolu- tion of HIV populations exposed to a recently developed antisense gene therapy, as well as a more conventional drug therapy. The detection of biologically rele- vant and plausible signals in both therapy studies demonstrates the effectiveness of the method.