Analysing postprandial amino acid responses in crossover studies with the aaresponse package for R

Area of Science:

• Nutritional Science
• Bioinformatics
• Software Development

Background:

• Growing interest in healthier, sustainable lifestyles drives research into plant-based proteins.
• Crossover trials are used to study nutrient uptake, but data analysis is complex.
• Objective and reproducible analysis is needed to streamline research processes.

Purpose of the Study:

• To introduce a novel open-source software package for analyzing amino acid uptake in human studies.
• To provide a streamlined, objective, and reproducible method for complex data analysis in nutritional research.
• To facilitate the comparison of different protein sources through advanced data visualization and statistical modeling.

Main Methods:

• Development of a bespoke software package for the R environment, named $$.
• Utilized mixed models to analyze parameters such as the area under the curve (AUC) for amino acid uptake.
• Employed parametric curves for fitting amino acid levels over time to enhance robustness and quality control.

Main Results:

• The software offers comprehensive visualization functions and supports consistent data curation.
• It enables robust comparison of amino acid uptake from various protein interventions.
• The use of parametric fitting improves the reliability and quality control of the analysis.

Conclusions:

• The developed software package $$ significantly enhances the objectivity and reproducibility of analyzing amino acid uptake data.
• Its features streamline complex data analysis, supporting research into healthier and more sustainable dietary options.
• The approach provides a robust framework for quality control and comparison of protein sources in human nutrition studies.