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An object-oriented framework for evolutionary pangenome analysis.

Ignacio Ferrés1,2, Gregorio Iraola1,2,3,4

  • 1Microbial Genomics Laboratory, Institut Pasteur Montevideo, Montevideo, Uruguay.

Cell Reports Methods
|April 27, 2022
PubMed
Summary
This summary is machine-generated.

Pagoo is a new R framework for bacterial pangenome analysis. It simplifies data handling, sharing, and reproducibility for exploring bacterial evolution and identifying host-adaptation markers.

Keywords:
Rbacterial comparative genomicsbacterial evolutiondata visualizationobject-oriented programmingpangenome analysispangenome reconstruction

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Area of Science:

  • Microbial Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Pangenome analysis is crucial for understanding bacterial molecular evolution.
  • Existing tools may lack integrated data handling and reproducibility features.
  • Efficient management of complex genomic and phenotypic data is needed.

Purpose of the Study:

  • Introduce Pagoo, an R framework for streamlined pangenome data management.
  • Provide tools for querying, subsetting, comparing, visualizing, and statistically analyzing pangenome data.
  • Demonstrate Pagoo's scalability and utility in real-world bacterial genomics studies.

Main Methods:

  • Developed Pagoo as an object-oriented R framework for pangenome data.
  • Utilized an encapsulated approach for storing molecular and phenotypic information.
  • Applied Pagoo to analyze 1,000 *Escherichia coli* genomes and a global *Campylobacter fetus* dataset.

Main Results:

  • Pagoo enables efficient, reproducible pangenome analysis within a single R environment.
  • Demonstrated Pagoo's scalability using a large dataset of *E. coli* genomes.
  • Identified evolutionary patterns and host-adaptation genomic markers in *C. fetus*.

Conclusions:

  • Pagoo offers a robust and user-friendly solution for bacterial pangenome analysis.
  • The framework facilitates reproducible research and discovery in microbial genomics.
  • Pagoo enhances the exploration of bacterial evolution and adaptation.