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mapPat: tracking pathogens evolution in space and time.

Erika Ferrandi1,2, Graziano Pesole1,3, Matteo Chiara2

  • 1Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Consiglio Nazionale delle Ricerche, Bari 70126, Italy.

Bioinformatics Advances
|February 19, 2025
PubMed
Summary
This summary is machine-generated.

mapPat is a new R Shiny application that interactively visualizes pathogen genomic data. This tool aids in monitoring pathogen evolution, variant spread, and informing public health decisions during infectious disease outbreaks.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Epidemiology

Background:

  • The COVID-19 pandemic underscored the critical need for robust genomic surveillance.
  • Effective genomic surveillance requires computational methods for managing and interpreting large datasets.
  • Monitoring pathogen evolution and spread is essential for public health.

Purpose of the Study:

  • To introduce mapPat, an R Shiny application for interactive genomic data visualization.
  • To provide a user-friendly dashboard for dynamic monitoring of pathogen evolution.
  • To enhance genomic surveillance strategies with advanced bioinformatics tools.

Main Methods:

  • Development of an R Shiny application named mapPat.
  • Implementation of interactive visualization features for genomic data.
  • Integration of geographic mapping and data visualization for temporal analysis.

Main Results:

  • mapPat enables the visualization of pathogen genomic data in space and time.
  • The application facilitates the dynamic monitoring of variants, lineages, and mutations.
  • Provides a fine-grained view of pathogen evolution and circulation patterns.

Conclusions:

  • mapPat is a valuable tool for genomic surveillance of pathogens.
  • The application aids in understanding pathogen evolution and informing public health responses.
  • mapPat contributes to the catalogue of bioinformatics methods for infectious disease monitoring.