Section: New Results

Feature selection in high dimensional regression problems for genomics

Participants: Julie Hamon, Clarisse Dhaenens (External collaborator : Julien Jacques)

In the context of genomic selection in animal breeding, an important objective consists in looking for explicative markers for a phe-notype under study. In order to deal with a high number of markers, we propose to use combinatorial optimization to perform variable selection. Results show that our approach outperforms some classical and widely used methods on simulated and “closed to real” datasets [76] . Familial relationships have also been used in this specific context and allow to improve results.