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Shiny-Calorie: a context-aware application for indirect calorimetry data analysis and visualization using R.

Stephan Grein1, Tabea Elschner2,3, Ronja Kardinal4

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Summary
This summary is machine-generated.

Shiny-Calorie is an open-source application that integrates and analyzes indirect calorimetry data from various platforms. This tool enhances reproducibility and transparency in metabolic phenotyping research.

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Area of Science:

  • Metabolic phenotyping
  • Bioinformatics
  • Animal research

Background:

  • Indirect calorimetry is crucial for metabolic phenotyping in pre-clinical research.
  • Existing platforms lack flexible, user-friendly software for data integration and analysis.
  • A unified approach is needed for diverse metabolic phenotyping data.

Purpose of the Study:

  • To introduce Shiny-Calorie, an open-source application for indirect calorimetry data.
  • To enable transparent data/metadata integration, statistical analysis, and visualization.
  • To streamline analysis workflows and improve reproducibility in metabolic studies.

Main Methods:

  • Developed Shiny-Calorie, an interactive application using GNU R.
  • Implemented support for standard data formats from major commercial platforms (TSE, Sable Systems, COSMED, CLAMS/Columbus).
  • Integrated advanced statistical methods for hypothesis testing and phenotype interpretation.

Main Results:

  • Shiny-Calorie supports diverse data formats and enables standardized data export.
  • The application facilitates intuitive exploration of complex, multi-modal longitudinal datasets.
  • It incorporates robust statistical methods for analyzing energy metabolism phenotypes.

Conclusions:

  • Shiny-Calorie provides a flexible, extensible, and user-friendly solution for indirect calorimetry data analysis.
  • The application enhances transparency and reproducibility in metabolic phenotyping.
  • It facilitates biologically meaningful interpretation of energy metabolism and expenditure.