A Mutagenetic Tree Hidden Markov Model for Longitudinal Clonal HIV Sequence Data

Details A Mutagenetic Tree Hidden Markov Model for Longitudinal Clonal HIV Sequence Data A Mutagenetic Tree Hidden Markov Model for Longitudinal Clonal HIV Sequence Data

2006-03-27

arxiv.org/abs/q-bio/0603031v1

Biostatistics 2007, Vol. 8, No. 1, 53-71

Biology

Quantitative Biology

Populations and Evolution

20 pages, 6 figures

Scientific paper

10.1093/biostatistics/kxj033

RNA viruses provide prominent examples of measurably evolving populations. In HIV infection, the development of drug resistance is of particular interest, because precise predictions of the outcome of this evolutionary process are a prerequisite for the rational design of antiretroviral treatment protocols. We present a mutagenetic tree hidden Markov model for the analysis of longitudinal clonal sequence data. Using HIV mutation data from clinical trials, we estimate the order and rate of occurrence of seven amino acid changes that are associated with resistance to the reverse transcriptase inhibitor efavirenz.

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