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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Updated: Jan 10, 2026

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PanGeneWhale - A dockerized Kotlin-based GUI platform for reproducible and user-friendly pangenomic analysis.

Walter de Barros Gomes Netto1, Saed Silva Sousa2, Sofia Mayumi Brandao Nakamaru3

  • 1Biological Engineering Laboratory, Guamá Science and Technology Park, Belém, Pará, Brazil.

Computational Biology and Chemistry
|November 21, 2025
PubMed
Summary

PanGeneWhale simplifies pangenomic analysis by integrating multiple tools into a user-friendly platform. This computational tool enhances accessibility and reproducibility for researchers studying microbial genomes.

Keywords:
BenchmarkingBioinformatics-ToolsDockerPangenomeReplicability

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Pangenomic analysis tools face challenges in usability, performance, and complexity.
  • These barriers limit accessibility and reproducibility, requiring advanced computational expertise.

Purpose of the Study:

  • To develop PanGeneWhale, a unified computational platform simplifying pangenomic analysis.
  • To enhance accessibility, reproducibility, and efficiency in large-scale genomic studies.

Main Methods:

  • Integration of multiple pangenomic analysis tools within a Docker container environment.
  • Development of an intuitive, cross-platform graphical user interface.
  • Validation using 50 Escherichia coli genomes and benchmarking of computational performance.

Main Results:

  • PanGeneWhale successfully integrates diverse tools, automating execution flows and ensuring reproducible results.
  • Benchmarking revealed performance disparities among tools, which PanGeneWhale addresses.
  • Identified and resolved critical usability issues like outdated dependencies and lack of GUIs.

Conclusions:

  • PanGeneWhale significantly improves the accessibility and efficiency of pangenomic analysis for researchers of all skill levels.
  • The platform enhances the practicality and reliability of large-scale genomic studies.
  • PanGeneWhale overcomes previous limitations, making advanced pangenomic analyses more manageable.