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OmNI: a modular open-source framework for interactive multi-omics data integration and visualization.

Grace Potter1, Jacob A Beierle2, Camron Bryant3

  • 1Program in Quantitative Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University, OR 97201, United States.

NAR Genomics and Bioinformatics
|January 12, 2026
PubMed
Summary
This summary is machine-generated.

Omics Notebook Interactive (OmNI) is an R-based framework for multi-omics data integration and analysis. It identifies conserved and strain-specific molecular responses to fentanyl in mouse brains.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Multi-omics data integration is crucial for understanding complex biological systems.
  • Existing tools often lack comprehensive integration capabilities and interactive visualizations.
  • Analyzing diverse omics data types requires flexible and scalable computational frameworks.

Purpose of the Study:

  • To introduce Omics Notebook Interactive (OmNI), an R-based framework for multi-omics data integration and analysis.
  • To demonstrate OmNI's utility in identifying molecular responses to fentanyl exposure in a mouse model.
  • To provide a modular and interactive platform for complex biological data exploration.

Main Methods:

  • OmNI utilizes customizable linear models for differential expression analysis.
  • A modified S-score statistic enables sensitive cross-omic layer integration.
  • Network and metabolomics data integration is performed with pathway enrichment analysis.
  • TMT18-based deep proteome and phosphoproteome analysis was conducted on mouse brain samples.

Main Results:

  • OmNI successfully integrated multi-omics data from genetically diverse mouse strains exposed to fentanyl.
  • The integrative S-score identified conserved differential signaling and interaction hubs across all strains.
  • Strain-specific molecular neuro-responses to fentanyl were revealed.
  • Interactive HTML reports and Cytoscape-compatible objects were generated.

Conclusions:

  • OmNI provides a powerful, scalable, and interactive framework for multi-omics data integration and analysis.
  • The framework facilitates the discovery of conserved and specific molecular mechanisms underlying biological responses.
  • OmNI is a valuable tool for researchers studying complex biological questions, including neurobiology and toxicology.