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

Bioinformatics advances

Authors: Stephan Grein, Tabea Elschner, Ronja Kardinal, Johanna Bruder, Akim Strohmeyer, Karthikeyan Gunasekaran, Jennifer Witt, Hildigunnur Hermannsdóttir, Janina Behrens, Mueez U-Din, Jiangyan Yu, Gerhard Heldmaier, Renate Schreiber, Jan Rozman, Markus Heine, Ludger Scheja, Anna Worthmann, Joerg Heeren, Dagmar Wachten, Kerstin Wilhelm-Jüngling, Alexander Pfeifer, Jan Hasenauer, Martin Klingenspor

MOTIVATION: Indirect calorimetry is the standard method for metabolic phenotyping of animal models in pre-clinical research, supported by mature experimental protocols and widely used commercial platforms. However, a flexible, extensible, and user-friendly software suite that enables standardized integration of data and metadata from diverse metabolic phenotyping platforms-followed by unified statistical analysis and visualization-remains absent.

RESULTS: We present Shiny-Calorie, an open-source interactive application for transparent data and metadata integration, comprehensive statistical data analysis, and visualization of indirect calorimetry datasets. Shiny-Calorie supports the majority of standard data formats across commercial metabolic phenotyping platforms, such as TSE and Sable Systems, COSMED platform and CLAMS/Columbus instruments, and provides export functionality of processed data into standardized formats. Built using GNU R with a reactive interface, Shiny-Calorie enables intuitive exploration of complex, multi-modal longitudinal datasets comprising categorical, continuous, ordinal, and count variables. The platform incorporates state-of-the-art statistical methods for robust hypothesis testing, thereby facilitating biologically meaningful interpretation of energy metabolism phenotypes, including resting metabolic rate and energy expenditure. Together, these features, streamline routine analysis workflows and enhances reproducibility and transparency in metabolic phenotyping studies.

AVAILABILITY AND IMPLEMENTATION: Shiny-Calorie is freely available at https://shiny.iaas.uni-bonn.de/Shiny-Calorie/. User documentation and source code are available at https://github.com/ICB-DCM/Shiny-Calorie. A docker image is available from https://hub.docker.com/r/stephanmg/Shiny-Calorie. Instructional screen recordings are available on https://www.youtube.com/@shiny-calorie.

© The Author(s) 2025. Published by Oxford University Press.

PMID: 41640623

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