Assessing genetic diversity by deep sequencing of mixed samples

N. Beerenwinkel, ETH Zürich

Wednesday, October 21
at 16.15, HG E 1.1

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response, vaccine design, and antiviral drug therapy. Recently developed deep sequencing technologies can be used for quantifying this diversity by direct sequencing of the mixed virus population. We present statistical and computational methods for the analysis of such sequence data. Inference of the underlying virus population from observed reads is based on a non-parametric Bayesian clustering approach and involves error correction, reconstruction of a minimal set of haplotypes that explain the data, and estimation of haplotype frequencies. We demonstrate our approach by analyzing simulated data and real HIV data.