Pieter Libin, Pieter Libin, Ewout Vanden Eynden, Ewout Vanden Eynden, Francesca Incardona, Francesca Incardona, Ann Nowé, Ann Nowé, Antonia Bezenchek, Antonia Bezenchek, Anders Sönnerborg, Anders Sönnerborg, Anne-Mieke Vandamme, Anne-Mieke Vandamme, EucoHIV Study Group, EucoHIV Study Group, Kristof Theys, Kristof Theys, Guy Baele, Guy Baele
Motivation: Clinicians, health officials and researchers are interested in the epidemic spread of pathogens in both space and time to support the optimization of intervention measures and public health policies. Large sequence databases of virus sequences provide an interesting opportunity to study this spread through phylogenetic analysis. To infer knowledge from large phylogenetic trees, potentially encompassing tens of thousands of virus strains, an efficient method for data exploration is required. The clades that are visited during this exploration should be annotated with strain characteristics (e.g. transmission risk group, tropism, drug resistance profile) and their geographic context.Results: PhyloGeoTool implements a visual method to explore large phylogenetic trees and to depict characteristics of strains and clades, including their geographic context, in an interactive way. PhyloGeoTool also provides the possibility to position new virus strains relative to the existing phylogenetic tree, allowing users to gain insight in the placement of such new strains without the need to perform a de novo reconstruction of the phylogeny.Availability and implementation: https://github.com/rega-cev/phylogeotool (Freely available: open source software project).Contact: phylogeotool@kuleuven.be.Supplementary information: Supplementary data are available at Bioinformatics online.
Libin, P, Vanden Eynden, E, Incardona, F, Nowé, A, Bezenchek, A, Sönnerborg, A, Vandamme, A-M, EucoHIV Study Group, Theys, K & Baele, G 2017, 'PhyloGeoTool: interactively exploring large phylogenies in an epidemiological context', Bioinformatics, vol. 33, no. 24, pp. 3993-3995. https://doi.org/10.1093/bioinformatics/btx535
Libin, P., Vanden Eynden, E., Incardona, F., Nowé, A., Bezenchek, A., Sönnerborg, A., Vandamme, A.-M., EucoHIV Study Group, Theys, K., & Baele, G. (2017). PhyloGeoTool: interactively exploring large phylogenies in an epidemiological context. Bioinformatics, 33(24), 3993-3995. https://doi.org/10.1093/bioinformatics/btx535
@article{292d915706e64345b2bdbe0c77e1bd04,
title = "PhyloGeoTool: interactively exploring large phylogenies in an epidemiological context",
abstract = "Motivation: Clinicians, health officials and researchers are interested in the epidemic spread of pathogens in both space and time to support the optimization of intervention measures and public health policies. Large sequence databases of virus sequences provide an interesting opportunity to study this spread through phylogenetic analysis. To infer knowledge from large phylogenetic trees, potentially encompassing tens of thousands of virus strains, an efficient method for data exploration is required. The clades that are visited during this exploration should be annotated with strain characteristics (e.g. transmission risk group, tropism, drug resistance profile) and their geographic context.Results: PhyloGeoTool implements a visual method to explore large phylogenetic trees and to depict characteristics of strains and clades, including their geographic context, in an interactive way. PhyloGeoTool also provides the possibility to position new virus strains relative to the existing phylogenetic tree, allowing users to gain insight in the placement of such new strains without the need to perform a de novo reconstruction of the phylogeny.Availability and implementation: https://github.com/rega-cev/phylogeotool (Freely available: open source software project).Contact: phylogeotool@kuleuven.be.Supplementary information: Supplementary data are available at Bioinformatics online.",
keywords = "Journal Article, Virus Diseases/epidemiology, Epidemiologic Methods, Humans, Software, Phylogeny, Computational Biology/methods, Databases, Nucleic Acid, Cluster Analysis",
author = "Pieter Libin and \{Vanden Eynden\}, Ewout and Francesca Incardona and Ann Now{\'e} and Antonia Bezenchek and Anders S{\"o}nnerborg and Anne-Mieke Vandamme and \{EucoHIV Study Group\} and Kristof Theys and Guy Baele",
note = "{\textcopyright} The Author(s) 2017. Published by Oxford University Press.",
year = "2017",
month = dec,
day = "15",
doi = "10.1093/bioinformatics/btx535",
language = "English",
volume = "33",
pages = "3993--3995",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "24",
}