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iHam and pyHam: visualizing and processing hierarchical orthologous groups.

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Summary
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We developed new tools to analyze gene family evolution using hierarchical orthologous groups (HOGs). These open-source methods simplify the visualization and programmatic processing of gene duplication and loss events across species.

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Area of Science:

  • Comparative genomics
  • Evolutionary biology
  • Bioinformatics

Background:

  • Gene family evolution is complex, involving gene duplications and losses.
  • Analyzing large numbers of genomes simultaneously complicates evolutionary studies.
  • Hierarchical Orthologous Groups (HOGs) represent gene sets descended from a common ancestor within a species clade.

Purpose of the Study:

  • To develop tools for manipulating and analyzing HOGs.
  • To facilitate the extraction, display, and interpretation of gene family history.
  • To make HOGs a more scalable and interpretable concept for cross-species gene relationships.

Main Methods:

  • Introduction of interactive HOG analysis method (iHam), a JavaScript widget for visualization.
  • Development of python HOG analysis method (pyHam), a Python library for programmatic processing.
  • Complementary open-source tools designed for ease of adoption.

Main Results:

  • iHam allows interactive exploration of gene family history encoded in HOGs.
  • pyHam enables programmatic processing of gene families for evolutionary analysis.
  • These tools simplify the interpretation of gene emergence, duplication, and loss events.

Conclusions:

  • The developed tools address the lack of accessible methods for HOG analysis.
  • iHam and pyHam enhance the scalability and interpretability of HOGs.
  • These resources facilitate a deeper understanding of gene family evolution across species.