ArticlePloS one2013
Mapping the shapes of phylogenetic trees from human and zoonotic RNA viruses.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Predicting Potential PRRSV-2 Variant Emergence through Phylogenetic Inference.Transboundary and emerging diseases · 2024Article
- Reconstructing early transmission networks of SARS-CoV-2 using a genomic mutation model.Zoological research · 2023Article
- Transmission cluster characteristics of global, regional, and lineage-specific SARS-CoV-2 phylogenies.IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- Ecological and evolutionary dynamics of multi-strain RNA viruses.Nature ecology & evolution · 2022Review
- Spatiotemporal Phylodynamics of Hepatitis C Among People Who Inject Drugs in India.Hepatology (Baltimore, Md.) · 2021Article
- Network science inspires novel tree shape statistics.PloS one · 2021Article
- Distance metrics for ranked evolutionary trees.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Statistical characteristics of amino acid covariance as possible descriptors of viral genomic complexity.Scientific reports · 2019Article
- Tree shape-based approaches for the comparative study of cophylogeny.Ecology and evolution · 2019Article
- Phylogenetic approach to recover integration dates of latent HIV sequences within-host.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- A Metric on Phylogenetic Tree Shapes.Systematic biology · 2018Article
- Phylogenetics of a Fungal Invasion: Origins and Widespread Dispersal of White-Nose Syndrome.mBio · 2017Article
- Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison.Molecular biology and evolution · 2017Article
- Reconstructing contact network parameters from viral phylogenies.Virus evolution · 2016Article
- Effects of memory on the shapes of simple outbreak trees.Scientific reports · 2016Article
- Phylodynamic Inference with Kernel ABC and Its Application to HIV Epidemiology.Molecular biology and evolution · 2015Article
- Measuring Asymmetry in Time-Stamped Phylogenies.PLoS computational biology · 2015Article
- Cost-effectiveness analysis along the continuum of HIV care: how can we optimize the effect of HIV treatment as prevention programs?Current HIV/AIDS reports · 2014Review
- Phylogenetic tree shapes resolve disease transmission patterns.Evolution, medicine, and public health · 2014Article
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Authors and funding
6 authors.
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Abstract
A phylogeny is a tree-based model of common ancestry that is an indispensable tool for studying biological variation. Phylogenies play a special role in the study of rapidly evolving populations such as viruses, where the proliferation of lineages is constantly being shaped by the mode of virus transmission, by adaptation to immune systems, and by patterns of human migration and contact. These processes may leave an imprint on the shapes of virus phylogenies that can be extracted for comparative study; however, tree shapes are intrinsically difficult to quantify. Here we present a comprehensive study of phylogenies reconstructed from 38 different RNA viruses from 12 taxonomic families that are associated with human pathologies. To accomplish this, we have developed a new procedure for studying phylogenetic tree shapes based on the 'kernel trick', a technique that maps complex objects into a statistically convenient space. We show that our kernel method outperforms nine different tree balance statistics at correctly classifying phylogenies that were simulated under different evolutionary scenarios. Using the kernel method, we observe patterns in the distribution of RNA virus phylogenies in this space that reflect modes of transmission and pathogenesis. For example, viruses that can establish persistent chronic infections (such as HIV and hepatitis C virus) form a distinct cluster. Although the visibly 'star-like' shape characteristic of trees from these viruses has been well-documented, we show that established methods for quantifying tree shape fail to distinguish these trees from those of other viruses. The kernel approach presented here potentially represents an important new tool for characterizing the evolution and epidemiology of RNA viruses.
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