Deep neural networks with controlled variable selection for the identification of putative causal genetic variants

1 code implementation • 29 Sep 2021 • Peyman H. Kassani, Fred Lu, Yann Le Guen, Zihuai He

The merit of the proposed method includes: (1) flexible modelling of the non-linear effect of genetic variants to improve statistical power; (2) multiple knockoffs in the input layer to rigorously control false discovery rate; (3) hierarchical layers to substantially reduce the number of weight parameters and activations to improve computational efficiency; (4) de-randomized feature selection to stabilize identified signals.

Computational Efficiency feature selection +1