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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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phylogatR: Phylogeographic data aggregation and repurposing.

Tara A Pelletier1, Danielle J Parsons2,3, Sydney K Decker2,3

  • 1Department of Biology, Radford University, Radford, Virginia, USA.

Molecular Ecology Resources
|June 24, 2022
PubMed
Summary
This summary is machine-generated.

The phylogatR database aggregates genetic data, enabling automated analysis for large-scale evolutionary and ecological studies. This tool facilitates data repurposing, making complex genetic analyses more accessible for researchers and educators.

Keywords:
biodiversity informaticsdata repurposinggenetic diversitymacrogeneticsopen science

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Area of Science:

  • Evolutionary Biology
  • Population Genetics
  • Ecology

Background:

  • Genetic diversity patterns reveal species' history, climate change responses, and dispersal capabilities.
  • Over 40,000 phylogeographic studies exist, generating millions of data points.
  • Synthesizing results from diverse studies is challenging due to varied methodologies.

Purpose of the Study:

  • To create a database (phylogatR) for efficient data repurposing and automated analysis.
  • To facilitate large-scale meta-analyses and educational genetic investigations.
  • To enhance the value of existing genetic data through accessible tools.

Main Methods:

  • Developed phylogatR database to aggregate data from various sources.
  • Implemented automated multiple sequence alignments and data curation.
  • Created software and web-based tools for data recycling and reanalysis.

Main Results:

  • phylogatR provides nearly ready-to-analyze genetic datasets for thousands of species.
  • The system automates complex data processing, saving time and resources.
  • Increased accessibility of big data for researchers and educators.

Conclusions:

  • phylogatR simplifies large meta-analyses addressing evolutionary and ecological questions.
  • The tool supports student and citizen science, broadening engagement with genetic data analysis.
  • Existing genetic data is made more valuable and accessible through phylogatR.