Séminaire Florian Privé "MAGNIFIC: Maximizing Genetic Findings and Prediction"

Lundi 9 décembre à 14h en salle Ruffié et TEAMS
Florian Privé is a researcher in statistical genetics, he is interested in using statistical learning to advance precision medicine. Specifically, he is developing tools (e.g. R package) to analyze very large datasets and methods to build predictive models based on large genetic data.
Since January 2022, Florian has a Senior Researcher position at Aarhus University (AU, Denmark), funded by a Lundbeck Foundation Fellowship (to Bjarni Vilhjálmsson).

ABSTRACT
As healthcare moves from a one-size-fits-all approach towards precision care, individual risk prediction is an important step in disease prevention and early detection. My proposed project aims to improve genetic predictions by developing better statistical tools that use results from genome-wide association studies (GWAS). These studies have mapped numerous genetic variants tied to traits like cancer or diabetes, which we can analyze collectively through polygenic scores (PGS) that estimate an individual's genetic risk. However, challenges remain in processing vast data, integrating biological context, and ensuring accuracy across diverse populations. To enhance PGS, I will develop methods that process millions of variants more efficiently, incorporate functional annotations and multi-ancestry data, and improve data quality control. These tools will increase the accuracy of genetic predictions across diverse populations, as well as contribute to the discovery of causal risk variants, and ultimately advance personalized medicine and reduce health disparities.