Probabilistic inference of viral quasispecies subject to recombination

Töpfer, Armin and Zagordi, Osvaldo and Prabhakaran, Sandhya and Roth, Volker and Halperin, Eran and Beerenwinkel, Niko. (2013) Probabilistic inference of viral quasispecies subject to recombination. Journal of computational biology, Vol. 20, H. 2. pp. 113-123.

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Official URL: http://edoc.unibas.ch/dok/A6194590

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RNA viruses exist in their hosts as populations of different but related strains. The virus population, often called quasispecies, is shaped by a combination of genetic change and natural selection. Genetic change is due to both point mutations and recombination events. We present a jumping hidden Markov model that describes the generation of viral quasispecies and a method to infer its parameters from next-generation sequencing data. The model introduces position-specific probability tables over the sequence alphabet to explain the diversity that can be found in the population at each site. Recombination events are indicated by a change of state, allowing a single observed read to originate from multiple sequences. We present a specific implementation of the expectation maximization (EM) algorithm to find maximum a posteriori estimates of the model parameters and a method to estimate the distribution of viral strains in the quasispecies. The model is validated on simulated data, showing the advantage of explicitly taking the recombination process into account, and applied to reads obtained from a clinical HIV sample.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Biomedical Data Analysis (Roth)
UniBasel Contributors:Roth, Volker and Prabhakaran, Sandhya
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Mary Ann Liebert
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:06 Dec 2013 09:35
Deposited On:06 Dec 2013 09:35

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