Utilizing Genetic Programming to Enhance Polygenic Risk Score Calculation
- Author(s)
- Martin Hurta, Jana Schwarzerová, Thomas Nägele, Wolfram Weckwerth, Valentine Provaznik, Lukas Sekanina
- Abstract
The polygenic risk score has proven to be a valuable tool for assessing an individual's genetic predisposition to phenotype (disease) within biomedicine in recent years. However, traditional regression-based methods for polygenic risk scores calculation have limitations that can impede their accuracy and predictive power. This study introduces an innovative approach to enhance polygenic risk scores calculation through the application of genetic programming. By harnessing the power of genetic programming, we aim to overcome the limitations of traditional regression techniques and improve the accuracy of polygenic risk scores predictions. Specifically, we showed that a polygenic risk score generated through Cartesian genetic programming yielded comparable or even more robust statistical distinctions between groups that we evaluated within three independent case studies.
- Organisation(s)
- Functional and Evolutionary Ecology, Research Platform Vienna Metabolomics Center
- External organisation(s)
- Brno University of Technology, Ludwig-Maximilians-Universität München
- Pages
- 3782-3787
- No. of pages
- 6
- DOI
- https://doi.org/10.1109/BIBM58861.2023.10385615
- Publication date
- 2023
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 106005 Bioinformatics
- Keywords
- ASJC Scopus subject areas
- Artificial Intelligence, Computer Science Applications, Computer Vision and Pattern Recognition, Automotive Engineering, Modelling and Simulation, Health Informatics
- Sustainable Development Goals
- SDG 3 - Good Health and Well-being
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/utilizing-genetic-programming-to-enhance-polygenic-risk-score-calculation(b817af67-1a40-4342-a713-8db11a53e311).html