A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Shiny-Calorie: a context-aware application for indirect calorimetry data analysis and visualization using R
Tekijät: Grein, Stephan; Elschner, Tabea; Kardinal, Ronja; Bruder, Johanna; Strohmeyer, Akim; Gunasekaran, Karthikeyan; Witt, Jennifer; Hermannsdóttir, Hildigunnur; Behrens, Janina; U-Din, Mueez; Yu, Jiangyan; Heldmaier, Gerhard; Schreiber, Renate; Rozman, Jan; Heine, Markus; Scheja, Ludger; Worthmann, Anna; Heeren, Joerg; Wachten, Dagmar; Wilhelm-Jüngling, Kerstin; Pfeifer, Alexander; Hasenauer, Jan; Klingenspor, Martin
Kustantaja: Oxford University Press
Julkaisuvuosi: 2026
Lehti: Bioinformatics Advances
Artikkelin numero: vbaf270
Vuosikerta: 6
Numero: 1
eISSN: 2635-0041
DOI: https://doi.org/10.1093/bioadv/vbaf270
Julkaisun avoimuus kirjaamishetkellä: Avoimesti saatavilla
Julkaisukanavan avoimuus : Kokonaan avoin julkaisukanava
Verkko-osoite: https://doi.org/10.1093/bioadv/vbaf270
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/509019953
Rinnakkaistallenteen lisenssi: CC BY
Rinnakkaistallennetun julkaisun versio: Kustantajan versio
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.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
Julkaisussa olevat rahoitustiedot:
This work was supported by the German Research Foundation [450149205 - TRR 333/1 (BATenergy) to S.G., T.E., R.K., K.G., J.W., H.H., J.B., L.S., D.W., A.W., J.He., K.W.-J., A.P., J.H., M.K.]. Author J.H. discloses financial support by the German Research Foundation under Germany’s Excellence Strategy EXC 2151—390873048 (ImmunoSensation2), EXC 2047—390685813 (Hausdorff Center for Mathematics) and a Schlegel Professorship by the University of Bonn; M.K. discloses funds from the Else Kröner Fresenius Foundation (2022_EKSP.51); J.R. discloses funds from the European Cooperation in Science and Technology Action CA20135; R.S. discloses funds from Austrian Science Fund (excellence cluster 10.55776/COE14) and University of Graz. There is no conflict of interest declared.
