@article {Cortopassi2022-wy,
	title = {Analysis of thermogenesis experiments with CalR},
	journal = {Methods Mol. Biol.},
	volume = {2448},
	year = {2022},
	pages = {43{\textendash}72},
	abstract = {Modern indirect calorimetry systems allow for high-frequency time series measurements of the factors affected by thermogenesis: energy intake and energy expenditure. These indirect calorimetry systems generate a flood of raw data recording oxygen consumption, carbon dioxide production, physical activity, and food intake among other factors. Analysis of these data requires time-consuming manual manipulation for formatting, data cleaning, quality control, and visualization. Beyond data handling, analyses of indirect calorimetry experiments require specialized statistical treatment to account for differential contributions of fat mass and lean mass to metabolic rates.Here we describe how to use the software package CalR version 1.2, to analyze indirect calorimetry data from three examples of thermogenesis, cold exposure, adrenergic agonism, and hyperthyroidism in mice, by providing standardized methods for reproducible research. CalR is a free online tool with an easy-to-use graphical user interface to import data files from the Columbus Instruments{\textquoteright} CLAMS, Sable Systems{\textquoteright} Promethion, and TSE Systems{\textquoteright} PhenoMaster. Once loaded, CalR can quickly visualize experimental results and perform basic statistical analyses. We present a framework that standardizes the data structures and analyses of indirect calorimetry experiments to provide reusable and reproducible methods for the physiological data affecting body weight.},
	keywords = {Adrenergic agonist, Body Weight, Cold exposure, Energy expenditure, Hyperthyroid, Indirect calorimetry, Metabolic rate, Thermogenesis, Weight Gain, Weight Loss},
	author = {Cortopassi, Marissa D and Ramachandran, Deepti and Rubio, William B and Hochbaum, Daniel and Sabatini, Bernardo L and Banks, Alexander S}
}
