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Protocol for HSDFinder: Identifying, annotating, categorizing, and visualizing duplicated genes in eukaryotic

Xi Zhang1, Yining Hu2, David Roy Smith1

  • 1Department of Biology, Western University, London, ON N6A 5B7, Canada.

STAR Protocols
|July 5, 2021
PubMed
Summary
This summary is machine-generated.

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HSDFinder identifies highly similar duplicated genes (HSDs) in eukaryotic genomes. This tool aids in comparing HSDs across species and visualizing their functional roles in KEGG pathways.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Gene duplications are common in eukaryotes, but quantifying highly similar duplicated genes (HSDs) is challenging.
  • Existing methods for HSD identification are often time-consuming and lack cross-species comparison capabilities.

Purpose of the Study:

  • To develop a novel computational tool, HSDFinder, for efficient identification, categorization, and visualization of HSDs in eukaryotic nuclear genomes.
  • To enable comparative analysis of HSDs across different species and their functional enrichment within Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.

Main Methods:

  • HSDFinder utilizes protein family domains and KEGG pathways for HSD identification.
  • The tool incorporates comparative analysis features for HSDs across multiple species.
Keywords:
BioinformaticsGenomicsSequence analysis

Related Experiment Videos

  • Results are visualized using heatmap plotting, categorized by KEGG pathway functional groups.
  • Main Results:

    • HSDFinder provides a comprehensive method for identifying and analyzing HSDs.
    • The tool facilitates cross-species comparisons of duplicated gene sets.
    • Functional insights into HSDs are gained through KEGG pathway visualization.

    Conclusions:

    • HSDFinder offers an efficient and versatile solution for studying HSDs in eukaryotic genomes.
    • The tool enhances our understanding of the evolutionary roles and functional significance of gene duplications.
    • HSDFinder supports comparative genomics research by enabling systematic analysis of HSDs and their pathway associations.