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HIV-Haplotype Inference using a Constraint-based Dirichlet Process Mixture Model

The recent introduction of the Deep Sequencing technology has led to a drastic increase in sequenced data but the limited length of these sequenced reads and non-negligible sequencing errors have also opened new statistical challenges in analysing the data.This work aims at analysing deep sequencing data obtained in a single run from genetically diverse samples, in particular from intra-host HIV populations: HIV exists in a single infected patient as quasispecies, a population of evolutionarily related haplotypes. We present an algorithm for identifying (an a priori unknown number of) these haplotypes in a sample and thereby quantifying the observed genetic diversity.