ArticlePLoS computational biology2021
Sampling bias and model choice in continuous phylogeography: Getting lost on a random walk.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
- One Health genomic surveillance reveals structured urban rabies transmission and major surveillance gaps.bioRxiv : the preprint server for biology · 2026Article
- Long-term spatiotemporal evolution of drug-resistant Mycobacterium tuberculosis in China.Nature communications · 2026Article
- SAASI: Sampling Aware Ancestral State Inference.Nature communications · 2026Article
- Global approaches to infectious disease surveillance and modeling.Nature medicine · 2026Review
- SERAPHIM 2.0: an extended toolbox for studying phylogenetically informed movements.Bioinformatics (Oxford, England) · 2026Article
- Phylogenetic insights into the transmission dynamics of arthropod-borne viruses.Nature reviews. Genetics · 2026Review
- The promise and challenge of spatial inference with the full ancestral recombination graph under Brownian motion.G3 (Bethesda, Md.) · 2025Article
- Navigating Sampling Bias in Discrete Phylogeographic Analysis: Assessing the Performance of an Adjusted Bayes Factor.Molecular biology and evolution · 2025Article
- Comparative performance of viral landscape phylogeography approaches.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Grains, trade and war in the multimodal transmission of Rice yellow mottle virus: An historical and phylogeographical retrospective.PLoS pathogens · 2025Article
- Exploiting Viral DNA Genomes to Explore the Dispersal History of African Swine Fever Genotype II Lineages in Europe.Genome biology and evolution · 2025Article
- Characterizing spatial epidemiology in a heterogeneous transmission landscape using the spatial transmission count statistic.Communications medicine · 2025Article
- Tracing more than two decades of Japanese encephalitis virus circulation in mainland China.Journal of virology · 2025Article
- Association of poultry vaccination with interspecies transmission and molecular evolution of H5 subtype avian influenza virus.Science advances · 2025Article
- Tracing the spread and phylogeography of foot-and-mouth disease virus across East and the Horn of Africa.Virus evolution · 2025Article
- Lost in the woods: shifting habitats can lead phylogeography astray.Virus evolution · 2025Article
- How fast are viruses spreading in the wild?PLoS biology · 2024Article
- Human outbreaks of a novel reassortant Oropouche virus in the Brazilian Amazon region.Nature medicine · 2024Article
- spread.gl: visualizing pathogen dispersal in a high-performance browser application.Bioinformatics (Oxford, England) · 2024Article
- Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phylogeographic inference allows reconstruction of past geographical spread of pathogens or living organisms by integrating genetic and geographic data. A popular model in continuous phylogeography-with location data provided in the form of latitude and longitude coordinates-describes spread as a Brownian motion (Brownian Motion Phylogeography, BMP) in continuous space and time, akin to similar models of continuous trait evolution. Here, we show that reconstructions using this model can be strongly affected by sampling biases, such as the lack of sampling from certain areas. As an attempt to reduce the effects of sampling bias on BMP, we consider the addition of sequence-free samples from under-sampled areas. While this approach alleviates the effects of sampling bias, in most scenarios this will not be a viable option due to the need for prior knowledge of an outbreak's spatial distribution. We therefore consider an alternative model, the spatial Λ-Fleming-Viot process (ΛFV), which has recently gained popularity in population genetics. Despite the ΛFV's robustness to sampling biases, we find that the different assumptions of the ΛFV and BMP models result in different applicabilities, with the ΛFV being more appropriate for scenarios of endemic spread, and BMP being more appropriate for recent outbreaks or colonizations.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.