ArticleProceedings of the National Academy of Sciences of the United States of America2021
Accounting for spatial sampling patterns in Bayesian phylogeography.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 30 citations in OpenAlex.
- SAASI: Sampling Aware Ancestral State Inference.Nature communications · 2026Article
- SERAPHIM 2.0: an extended toolbox for studying phylogenetically informed movements.Bioinformatics (Oxford, England) · 2026Article
- Optimizing genomic sampling for demographic and epidemiological inference with Markov decision processes.Genetics · 2026Article
- VirPhyKit: An Integrated Toolkit for Viral Phylogeographic Analysis.Ecology and evolution · 2025Article
- Navigating Sampling Bias in Discrete Phylogeographic Analysis: Assessing the Performance of an Adjusted Bayes Factor.Molecular biology and evolution · 2025Article
- Grains, trade and war in the multimodal transmission of Rice yellow mottle virus: An historical and phylogeographical retrospective.PLoS pathogens · 2025Article
- How fast are viruses spreading in the wild?PLoS biology · 2024Article
- Modeling the velocity of evolving lineages and predicting dispersal patterns.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- COVID-19 pandemic interventions reshaped the global dispersal of seasonal influenza viruses.Science (New York, N.Y.) · 2024Article
- Modeling the velocity of evolving lineages and predicting dispersal patterns.bioRxiv : the preprint server for biology · 2024Article
- Data integration in Bayesian phylogenetics.Annual review of statistics and its application · 2023Article
- Impact and mitigation of sampling bias to determine viral spread: Evaluating discrete phylogeography through CTMC modeling and structured coalescent model approximations.Virus evolution · 2023Article
- Phylodynamic analysis of the highly pathogenic avian influenza H5N8 epidemic in France, 2016-2017.Transboundary and emerging diseases · 2022Article
- Article
- SPREAD 4: online visualisation of pathogen phylogeographic reconstructions.Virus evolution · 2022Article
- Epidemiological inference from pathogen genomes: A review of phylodynamic models and applications.Virus evolution · 2022Review
- The impact of sampling bias on viral phylogeographic reconstruction.PLOS global public health · 2022Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Statistical phylogeography provides useful tools to characterize and quantify the spread of organisms during the course of evolution. Analyzing georeferenced genetic data often relies on the assumption that samples are preferentially collected in densely populated areas of the habitat. Deviation from this assumption negatively impacts the inference of the spatial and demographic dynamics. This issue is pervasive in phylogeography. It affects analyses that approximate the habitat as a set of discrete demes as well as those that treat it as a continuum. The present study introduces a Bayesian modeling approach that explicitly accommodates for spatial sampling strategies. An original inference technique, based on recent advances in statistical computing, is then described that is most suited to modeling data where sequences are preferentially collected at certain locations, independently of the outcome of the evolutionary process. The analysis of georeferenced genetic sequences from the West Nile virus in North America along with simulated data shows how assumptions about spatial sampling may impact our understanding of the forces shaping biodiversity across time and space.
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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.