ArticlePLoS computational biology2025
wavess: An R package for simulation of adaptive within-host virus sequence evolution.
Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- wavess 1.2: Presenting an HLA-aware within-host virus sequence simulation framework.bioRxiv : the preprint server for biology · 2026Article
- wavess 1.2: presenting an HLA-aware within-host virus sequence simulation framework.Bioinformatics advances · 2026Article
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Authors and funding
6 authors.
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Abstract
Simulating within-host virus sequence evolution allows for the investigation of factors such as the role of recombination in virus diversification and the impact of selective pressures on virus evolution. Here, we provide a new software to simulate virus within-host evolution called wavess (within-host adaptive virus evolution sequence simulator), a discrete-time individual-based model and a corresponding user-friendly R package. The underlying model simulates recombination, a latent infected cell reservoir, and three forms of selection: conserved sites fitness and replicative fitness in comparison to a reference sequence, and immune fitness including cross-reactivity imposed by a co-evolving immune response. In the R package, we also provide functions to generate model inputs from empirical data, as well as functions to analyze the simulation outputs. At user-defined time points, the software returns various counts related to the virus population(s) and a set of sampled virus sequences. We applied this model to investigate the selection pressures on HIV-1 env sequences longitudinally collected from 11 individuals. The best-fitting immune cost differed across individuals, mirroring the real-world expectation of heterogeneous immune responses among human hosts. Furthermore, the phylogenies reconstructed from these simulated sequences were similar to the phylogenies reconstructed from the real sequences for all summary statistics tested. To our knowledge, compared to other similar models, wavess has been more rigorously validated against real within-host virus sequences, and is the first to be implemented as an R package. The wavess R package can be downloaded from https://github.com/MolEvolEpid/wavess.
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