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Updated: May 29, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics.

Filip Bielejec¹, Andrew Rambaut, Marc A Suchard

¹Rega Institute for Medical Research, Clinical and Epidemiological Virology Section, Katholieke Universiteit Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be

Bioinformatics (Oxford, England)

|September 14, 2011

Summary

SPREAD is a new software application for analyzing and visualizing Bayesian phylogeographic reconstructions. It aids in understanding historical diffusion patterns by mapping phylogenies and spatial data, offering compelling visualizations.

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Area of Science:

Evolutionary biology
Genetics
Bioinformatics

Background:

Phylogeographic reconstructions are crucial for understanding species' evolutionary history and spatial spread.
Analyzing complex spatial-temporal diffusion patterns requires specialized computational tools.

Purpose of the Study:

To introduce SPREAD, a user-friendly, cross-platform application for analyzing and visualizing Bayesian phylogeographic reconstructions.
To facilitate the incorporation of spatial-temporal diffusion into phylogenetic analyses.

Main Methods:

SPREAD analyzes phylogenies annotated with discrete and continuous spatial information.
It utilizes Bayesian stochastic search variable selection for hypothesis testing.
The software leverages multicore architectures for efficient processing of large datasets.

Main Results:

SPREAD generates visualizations of phylogenies with spatial diffusion through time.
It exports data to Keyhole Markup Language (KML) for animation in virtual globes.
Bayes factor calculations are implemented to evaluate diffusion hypotheses.

Conclusions:

SPREAD provides a comprehensive tool for phylogeographic analysis and visualization.
The software enhances the interpretability of spatial-temporal diffusion patterns in evolutionary studies.
It is freely available and open-source, promoting wider adoption in the scientific community.