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  1. Home
  3. Iseetree: Interactive Explorer For Hierarchical Data.
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  3. Iseetree: Interactive Explorer For Hierarchical Data.

Related Experiment Video

The ITS2 Database
16:17

The ITS2 Database

Published on: March 12, 2012

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iSEEtree: interactive explorer for hierarchical data.

Giulio Benedetti1, Ely Seraidarian1, Theotime Pralas1

  • 1Department of Computing, Faculty of Technology, University of Turku, Turku FI-20014, Finland.

Bioinformatics Advances
|May 23, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

iSEEtree is a new R package that simplifies the analysis of hierarchical data, particularly for microbiome studies. It offers a visual interface, reducing the need for programming expertise to explore complex biological datasets.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Visualization

Background:

  • Hierarchical data structures are essential for analyzing complex systems, notably in microbiome research using phylogenetic trees.
  • The R/Bioconductor ecosystem offers a reproducible framework for hierarchical data via the TreeSummarizedExperiment container.
  • Existing frameworks necessitate programming skills, posing a barrier to entry for some researchers.

Purpose of the Study:

  • To develop an accessible tool for exploring hierarchical data structures.
  • To lower the technical barrier for analyzing TreeSummarizedExperiment objects.
  • To extend interactive visualization capabilities to hierarchical data.

Main Methods:

  • Development of the iSEEtree R package.
  • Implementation of a visual interface for TreeSummarizedExperiment objects.
  • Demonstration of functionality using microbiome analysis datasets.

    • Main Results:

    • iSEEtree provides an interactive graphical user interface for exploring hierarchical data.
    • The package enables users to analyze complex multi-table data without extensive R programming knowledge.
    • iSEEtree successfully facilitates microbiome data exploration through its visual interface.

    Conclusions:

    • iSEEtree significantly enhances the accessibility of hierarchical data analysis.
    • The package empowers researchers, especially in microbiome studies, to explore complex data visually.
    • iSEEtree expands interactive data exploration to hierarchical structures within the R environment.