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Updated: May 2, 2026

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xOmicsShiny: an R Shiny application for cross-omics data analysis and pathway mapping.

Benbo Gao1, Yu H Sun1, Xinmin Zhang2

  • 1Research and Development, Biogen Inc., Cambridge, MA 02142, United States.

Bioinformatics Advances
|May 29, 2025
PubMed
Summary
This summary is machine-generated.

xOmicsShiny is a new R Shiny application for biologists to explore multi-omics data, integrating transcriptomics, proteomics, and metabolomics for pathway-level insights. It offers various analyses and visualizations, enhancing biological discovery.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Exploring multi-omics datasets (transcriptomics, proteomics, metabolomics, lipidomics) is crucial for biological discovery.
  • Existing tools often lack comprehensive integration and pathway-level analysis capabilities.
  • Efficient visualization and analysis of complex omics data remain a challenge for researchers.

Purpose of the Study:

  • To develop xOmicsShiny, an R Shiny application for comprehensive exploration of multi-omics data.
  • To facilitate biological insight discovery at the pathway level by integrating diverse omics datasets.
  • To provide a user-friendly platform with advanced analytical and visualization tools for omics data.

Main Methods:

  • Development of a feature-rich R Shiny application, xOmicsShiny.
  • Implementation of a data merging feature for cross-omics data integration.
  • Integration of multiple pathway databases (WikiPathways, Reactome, KEGG) for pathway mapping.
  • Inclusion of various analytical modules: PCA, Volcano plot, Venn Diagram, Heatmap, WGCNA, and clustering.
  • Modular design to enhance performance and extensibility.

Main Results:

  • xOmicsShiny enables flexible exploration of integrated omics data (transcriptomics, proteomics, metabolomics, lipidomics).
  • The application provides comprehensive pathway mapping across multiple databases.
  • It offers a suite of standard omics analyses and visualizations, including interactive and publication-ready outputs.
  • The modular design addresses slow loading issues common in R Shiny tools.

Conclusions:

  • xOmicsShiny is a powerful, versatile tool for biologists to explore multi-omics data and uncover biological insights.
  • Its integrated approach and pathway-centric analysis enhance the understanding of complex biological systems.
  • The application's design promotes community expansion and future development.