|
Project properties |
|
| Title | Optimizing Indirect Calorimetry Data Analysis and Presentation with R |
| Group | Systems and Synthetic Biology |
| Project type | thesis |
| Credits | 36 |
| Supervisor(s) | Evert van Schothorst (HAP), Jo-lene de Deugd (HAP), Edoardo Saccenti (SSB) |
| Examiner(s) | Edoardo Saccenti |
| Contact info | Rob Smith robert1.smith@wur.nl |
| Begin date | 2024/02/02 |
| End date | |
| Description | Research at the Human and Animal Physiology (HAP) group at Wageningen University is focused on energy metabolism. A compromised energy metabolism is a central component of diet- and age-related diseases. At HAP, we use in most of our preclinical (mouse) studies a non-invasive indirect calorimetry system. Simply said, this system measures non-invasive, real-time, continuous inhaled and exhaled air in order to determine energy expenditure (metabolic rate) and substrate usage at whole body level based on measurements of gases. Large datasets are generated which also include more parameters measured by the system (e.g. voluntary activity and food/drink intake).
Currently, we perform the QC and data analyses mainly in Excel, and the visualization/plotting of curves and data together with appropriate statistics using GraphPad Prism. However, the objective of this thesis project is to create a reproducible workflow with standardized analyses and statistical comparisons in R. In this project, you will be guided by Edoardo Saccenti from SSB who will provide support with the development of the R script(s) and supervisors from HAP who will help in tailoring the script(s) to the project's practical requirements. References Examples of recent work at HAP with the indirect calorimetry system: Fernandez-Calleja, J. M. S., et al. (2018). "Non-invasive continuous real-time in vivo analysis of microbial hydrogen production shows adaptation to fermentable carbohydrates in mice." Scientific Reports 8(1): 15351. doi: 10.1038/s41598-018-33619-0 Fernández-Calleja, J. M. S., et al. (2019). "Extended indirect calorimetry with isotopic CO2 sensors for prolonged and continuous quantification of exogenous vs. total substrate oxidation in mice." Scientific Reports 9(1). doi: 10.1038/s41598-019-47977-w Example of how R could be used: Mina, A. I., et al. (2018). "CalR: A Web-Based Analysis Tool for Indirect Calorimetry Experiments." Cell Metabolism 28(4): 656-666.e651. doi: 10.1016/j.cmet.2018.06.019 |
| Used skills | - Experience in handling and analysing large datasets
- Familiarity and affinity with physiological research - Hands-on experience in data analysis and script writing for an applied, real-world scenario |
| Requirements | - Knowledge or R and some familiarity with basic data analysis tools
- Physiology knowledge is useful but not required - Must have attended and passed Molecular Systems Biology SSB |