iSEEtree: interactive explorer for hierarchical data

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.