MinPD: distance-based phylogenetic analysis and recombination detection of serially-sampled HIV quasispecies

A new computational method to study within-host viral evolution is explored to better understand the evolution and pathogenesis of viruses. Traditional phylogenetic tree methods are better suited to study relationships between contemporaneous species, which appear as leaves of a phylogenetic tree. However, viral sequences are often sampled serially from a single host. Consequently, data may be available at the leaves as well as the internal nodes of a phylogenetic tree. Recombination may further complicate the analysis. Such relationships are not easily expressed by traditional phylogenetic methods. We propose a new algorithm, called MinPD, based on minimum pairwise distances. Our algorithm uses multiple distance matrices and correlation rules to output a MinPD tree or network. We test our algorithm using extensive simulations and apply it to a set of HIV sequence data isolated from one patient over a period often years. The proposed visualization of the phylogenetic tree/network further enhances the benefits of our methods.