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cOmicsArt-a customizable Omics Analysis and reporting tool.

Lea Seep1, Paul Jonas Jost1, Clivia Lisowski2

  • 1Computational Biology, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn 53115, Germany.

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|May 19, 2025
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Summary
This summary is machine-generated.

The customizable Omics Analysis and reporting tool (cOmicsArt) integrates graphical user interface (GUI) analysis with R, enhancing collaboration and reproducibility for omics data. This tool supports researchers from novice to expert levels, facilitating seamless transitions and advanced customizations.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Science

Background:

  • Increasing availability of bulk-omic data requires enhanced collaboration between experimental and computational researchers.
  • Existing graphical user interface (GUI) tools for omics data analysis are limited by pre-implemented methods and lack GUI-independent reproducibility.
  • Transitioning from GUI tools to custom code for omics data analysis is often challenging due to limited support for reproducibility.

Purpose of the Study:

  • To introduce cOmicsArt, a customizable omics analysis and reporting tool designed to improve collaboration.
  • To provide a platform that integrates GUI-based analysis with R for enhanced flexibility and reproducibility.
  • To support researchers of all skill levels in performing exploratory and statistical analyses of omics data.

Main Methods:

  • Development of cOmicsArt, a tool featuring a user-friendly GUI for exploratory and statistical analyses.
  • Integration of interactive visualizations and automatic documentation within the GUI.
  • Provision of downloadable R scripts and results to ensure reproducibility and facilitate seamless integration with R.

Main Results:

  • cOmicsArt enables user-friendly omics data analysis through an integrated GUI and R environment.
  • The tool ensures reproducibility via downloadable R scripts and supports customization for advanced analyses.
  • cOmicsArt serves as a versatile educational tool, guiding users from GUI-based analysis to R coding.

Conclusions:

  • cOmicsArt enhances collaboration and reproducibility in omics data analysis by bridging GUI-based approaches and R programming.
  • The tool's flexibility supports both novice and experienced researchers, as well as educational purposes.
  • cOmicsArt provides a robust foundation for diverse omics data analysis needs and further customization.