ArticleGenetics2015
A framework for inferring fitness landscapes of patient-derived viruses using quasispecies theory.
Article in Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Optimal control and the dynamics of ancestral lineages.Genetics · 2026Article
- Hierarchical genotype networks and incipient ecological speciation in Q[Formula: see text] phage quasispecies.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks.Nature communications · 2024Article
- Observational
- Inference of mutability landscapes of tumors from single cell sequencing data.PLoS computational biology · 2020Article
- Estimating the predictability of cancer evolution.Bioinformatics (Oxford, England) · 2019Article
- Inference of clonal selection in cancer populations using single-cell sequencing data.Bioinformatics (Oxford, England) · 2019Article
- DISSEQT-DIStribution-based modeling of SEQuence space Time dynamics.Virus evolution · 2019Article
- Modeling Cumulative Biological Phenomena with Suppes-Bayes Causal Networks.Evolutionary bioinformatics online · 2018Article
- Article
- Comparison of error correction algorithms for Ion Torrent PGM data: application to hepatitis B virus.Scientific reports · 2017Article
- Discovering Complete Quasispecies in Bacterial Genomes.Genetics · 2017Article
- Article
- How Good Are Statistical Models at Approximating Complex Fitness Landscapes?Molecular biology and evolution · 2016Article
- Barrier-Independent, Fitness-Associated Differences in Sofosbuvir Efficacy against Hepatitis C Virus.Antimicrobial agents and chemotherapy · 2016Article
- Fitness Inference from Short-Read Data: Within-Host Evolution of a Reassortant H5N1 Influenza Virus.Molecular biology and evolution · 2015Article
Corrections and comments
- Erratum issuedCorrigendum.2015
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fitness is a central quantity in evolutionary models of viruses. However, it remains difficult to determine viral fitness experimentally, and existing in vitro assays can be poor predictors of in vivo fitness of viral populations within their hosts. Next-generation sequencing can nowadays provide snapshots of evolving virus populations, and these data offer new opportunities for inferring viral fitness. Using the equilibrium distribution of the quasispecies model, an established model of intrahost viral evolution, we linked fitness parameters to the composition of the virus population, which can be estimated by next-generation sequencing. For inference, we developed a Bayesian Markov chain Monte Carlo method to sample from the posterior distribution of fitness values. The sampler can overcome situations where no maximum-likelihood estimator exists, and it can adaptively learn the posterior distribution of highly correlated fitness landscapes without prior knowledge of their shape. We tested our approach on simulated data and applied it to clinical human immunodeficiency virus 1 samples to estimate their fitness landscapes in vivo. The posterior fitness distributions allowed for differentiating viral haplotypes from each other, for determining neutral haplotype networks, in which no haplotype is more or less credibly fit than any other, and for detecting epistasis in fitness landscapes. Our implemented approach, called QuasiFit, is available at http://www.cbg.ethz.ch/software/quasifit.
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