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Estimating the dynamics and dependencies of accumulating mutations with applications to HIV drug resistance.

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Montazeri Hesam, Günthard Huldrych F, Yang Wan-Lin, Kouyos Roger, Beerenwinkel Niko,
Project Swiss HIV Cohort Study (SHCS)
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Original article (peer-reviewed)

Journal Biostatistics (Oxford, England)
Volume (Issue) 16(4)
Page(s) 713 - 26
Title of proceedings Biostatistics (Oxford, England)
DOI 10.1093/biostatistics/kxv019

Open Access

URL https://doi.org/10.1093/biostatistics/kxv019
Type of Open Access Publisher (Gold Open Access)

Abstract

We introduce a new model called the observed time conjunctive Bayesian network (OT-CBN) that describes the accumulation of genetic events (mutations) under partial temporal ordering constraints. Unlike other CBN models, the OT-CBN model uses sampling time points of genotypes in addition to genotypes themselves to estimate model parameters. We developed an expectation-maximization algorithm to obtain approximate maximum likelihood estimates by accounting for this additional information. In a simulation study, we show that the OT-CBN model outperforms the continuous time CBN (CT-CBN) (Beerenwinkel and Sullivant, 2009. Markov models for accumulating mutations. Biometrika 96: (3), 645-661), which does not take into account individual sampling times for parameter estimation. We also show superiority of the OT-CBN model on several datasets of HIV drug resistance mutations extracted from the Swiss HIV Cohort Study database.
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