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TreeSnatcher: coding trees from images.

Thomas Laubach1, Arndt von Haeseler

  • 1Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, Dr-Bohr-Gasse 9/6, A-1030 Vienna, Austria.

Bioinformatics (Oxford, England)
|September 26, 2007
PubMed
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TreeSnatcher is a novel JAVA application that semi-automatically recognizes multifurcating phylogenetic trees from pixel images. This tool analyzes tree topology and metrics, generating Newick tree code for evolutionary analysis.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Phylogenetics

Background:

  • Phylogenetic tree reconstruction is crucial for understanding evolutionary relationships.
  • Manual analysis of phylogenetic trees from images can be time-consuming and error-prone.
  • Automated tools are needed to efficiently process and analyze tree data.

Purpose of the Study:

  • To introduce TreeSnatcher, a GUI-driven JAVA application for semi-automatic recognition of multifurcating phylogenetic trees from pixel images.
  • To provide a tool that analyzes both the topology and metrics of trees depicted in images.
  • To generate a standardized Newick tree code representing the tree structure, optionally including branch lengths.

Main Methods:

  • The TreeSnatcher application utilizes image analysis algorithms in a multi-stage process.

Related Experiment Videos

  • It accepts pixel image files as input for tree recognition.
  • The software is developed in JAVA and runs on multiple operating systems (Mac OS X, UNIX/Linux, Windows).

    • Main Results:

    • TreeSnatcher successfully performs semi-automatic recognition of multifurcating phylogenetic trees.
    • The application analyzes tree topology and metrics, outputting a Newick tree code.
    • It can process trees with 100 or more leaves in a matter of seconds.

    Conclusions:

    • TreeSnatcher offers an efficient solution for extracting phylogenetic information from image data.
    • The tool aids in the semi-automatic analysis of complex tree structures.
    • Its availability and cross-platform compatibility facilitate its use in evolutionary studies.