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OmicsQ: a user-friendly platform for interactive quantitative omics data analysis.

Xuan-Tung Trinh1, André Abrantes da Costa1,2, David Bouyssié3,4

  • 1Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark.

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Summary
This summary is machine-generated.

OmicsQ is a new web platform simplifying quantitative omics data analysis. It handles complex datasets, missing values, and integrates with other tools for deep biological insights.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Science

Background:

  • High-throughput omics technologies produce complex, high-dimensional datasets.
  • These datasets often contain missing values and variable variances, complicating analysis.
  • Existing analytical tools are often programming-based, limiting accessibility for non-computational researchers.

Purpose of the Study:

  • To develop an accessible, web-based platform for streamlined quantitative omics data analysis.
  • To provide an intuitive interface integrating statistical processing and visualization.
  • To facilitate deep biological interpretation of complex omics data.

Main Methods:

  • Developed OmicsQ, an interactive, R and Shiny-based web platform.
  • Integrated robust batch correction, automated experimental design annotation, and missing data handling without imputation.
  • Enabled seamless interaction with external applications for statistical testing, clustering, and pathway enrichment.

Main Results:

  • OmicsQ offers a user-friendly, browser-based interface for omics data analysis.
  • The platform handles data complexity, missing values, and batch effects robustly.
  • OmicsQ integrates with tools like PolySTest, VSClust, and ComplexBrowser for comprehensive analysis.

Conclusions:

  • OmicsQ provides a flexible and broadly applicable workflow for omics data analysis.
  • The platform enhances accessibility for researchers without extensive computational expertise.
  • OmicsQ supports the complete process from data import to biological interpretation.