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Abstract
With the evolution of next generation sequencing (NGS) technologies, whole-genome sequencing of bacterial isolates is increasingly employed to investigate epidemiology. Phylogenetic analysis is the common method for using NGS data, usually for comparing closeness between bacterial isolates to detect probable outbreaks. However, interpreting a phylogenetic tree is not easy without training in evolutionary biology. Therefore, developing an easy-to-use tool that can assist people who wish to use a phylogenetic tree to investigate epidemiological relatedness is crucial. In this paper, we present a tool called OutbreakFinder that can accept a distance matrix in csv format; alignment files from Lyve-SET, Parsnp, and ClustalOmega; and a tree file in Newick format as inputs to compute a cluster-labeled two-dimensional plot based on multidimensional-scaling dimension reduction coupled with affinity propagation clustering. OutbreakFinder can be downloaded for free at https://github.com/skypes/Newton-method-MDS.
Highlights
Phylogenetic trees are widely used in public health to infer the molecular epidemiology of infectious diseases (Hall & Barlow, 2006; Pybus, Fraser & Rambaut, 2013)
We present a tool called OutbreakFinder that can assist in outbreak detection; this tool can help users to plot an multidimensional scaling (MDS) plot with a cluster labeled from a distance matrix or alignment files from Lyve-SET (Katz et al, 2017), Parsnp (Treangen et al, 2014), or ClustalOmega (Sievers & Higgins, 2014)
We present a visualization tool named OutbreakFinder that can show relationships among compared bacterial isolates on a two-dimensional MDS plot from distance matrix calculation or tree transformation
Summary
Phylogenetic trees are widely used in public health to infer the molecular epidemiology of infectious diseases (Hall & Barlow, 2006; Pybus, Fraser & Rambaut, 2013). We introduced a dimension reduction approach named multidimensional scaling (MDS) to transform a phylogenetic tree into a two-dimensional plot and subsequently apply affinity propagation (AP) (Frey & Dueck, 2007) for clustering. This approach can facilitate rapid identification of relationships among compared bacterial isolates for investigation of clusters. We present a tool called OutbreakFinder that can assist in outbreak detection; this tool can help users to plot an MDS plot with a cluster labeled from a distance matrix or alignment files from Lyve-SET (Katz et al, 2017), Parsnp (Treangen et al, 2014), or ClustalOmega (Sievers & Higgins, 2014)
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