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Related Concept Videos

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Related Experiment Video

Updated: Apr 12, 2026

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
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PhyTB: Phylogenetic tree visualisation and sample positioning for M. tuberculosis.

Ernest D Benavente1,2, Francesc Coll3, Nick Furnham4

  • 1Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel St, London, UK. ernest.diezbenavente@lshtm.ac.uk.

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|May 14, 2015
PubMed
Summary

This study introduces PhyTB, a web tool for visualizing Mycobacterium tuberculosis genomic variation on phylogenetic trees. It aids in classifying strains and understanding disease transmission patterns.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Phylogenetic analysis is crucial for understanding bacterial evolution, disease outbreaks, and transmission.
  • Whole genome sequencing reveals genomic variation in bacterial strains, aiding classification.
  • A lack of interactive tools hinders the visualization of bacterial genomic variation within phylogenetic trees.

Purpose of the Study:

  • To develop a user-interactive, web-based tool for visualizing Mycobacterium tuberculosis genomic variation.
  • To facilitate the identification of clade-informative polymorphisms in M. tuberculosis.
  • To contextualize genomic data within epidemiological and geographical settings.

Main Methods:

  • Development of PhyTB, a web-based application for phylogenetic tree visualization.
  • Enabling upload of Variant Call Format (VCF) files to position samples within a phylogenetic tree.
  • Incorporating a map view to summarize the geographical distribution of alleles and strain types.

Main Results:

  • PhyTB was developed and demonstrated using sequence data from 1,601 M. tuberculosis isolates.
  • The tool allows for phylogenetic tree visualization and identification of M. tuberculosis clade-informative polymorphisms.
  • A map view effectively summarizes the geographical distribution of alleles and strain types.

Conclusions:

  • PhyTB effectively contextualizes M. tuberculosis genomic variation within epidemiological, geographical, and phylogenetic frameworks.
  • Future enhancements could include incorporating large variants and phenotypic data for genotype-phenotype association studies.
  • The source code is available for developing similar tools for other organisms.