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• W4312191616 abstract "The composition of the latent human immunodeficiency virus 1 (HIV-1) reservoir is shaped by when proviruses integrated into host genomes. These integration dates can be estimated by phylogenetic methods like root-to-tip (RTT) regression. However, RTT does not accommodate variation in the number of mutations over time, uncertainty in estimating the molecular clock, or the position of the root in the tree. To address these limitations, we implemented a Bayesian extension of RTT as an R package (bayroot), which enables the user to incorporate prior information about the time of infection and start of antiretroviral therapy. Taking an unrooted maximum likelihood tree as input, we use a Metropolis-Hastings algorithm to sample from the joint posterior distribution of three parameters (the rate of sequence evolution, i.e., molecular clock; the location of the root; and the time associated with the root). Next, we apply rejection sampling to this posterior sample of model parameters to simulate integration dates for HIV proviral sequences. To validate this method, we use the R package treeswithintrees (twt) to simulate time-scaled trees relating samples of actively and latently infected T cells from a single host. We find that bayroot yields significantly more accurate estimates of integration dates than conventional RTT under a range of model settings." @default.
• W4312191616 created "2023-01-04" @default.
• W4312191616 creator A5004110504 @default.
• W4312191616 creator A5058253138 @default.
• W4312191616 creator A5084972791 @default.
• W4312191616 date "2022-12-21" @default.
• W4312191616 modified "2023-10-16" @default.
• W4312191616 title "bayroot: Bayesian sampling of HIV-1 integration dates by root-to-tip regression" @default.
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• W4312191616 doi "https://doi.org/10.1093/ve/veac120" @default.
• W4312191616 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36632480" @default.
• W4312191616 hasPublicationYear "2022" @default.
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