Distributed transformer for high order epistasis detection in large-scale datasets.

ABSTRACT: Understanding the genetic basis of complex diseases is one of the most important challenges in current precision medicine. To this end, Genome-Wide Association Studies aim to correlate Single Nucleotide Polymorphisms (SNPs) to the presence or absence of certain traits. However, these studies do not consider interactions between several SNPs, known as epistasis, which explain most genetic diseases. Analyzing SNP combinations to detect epistasis is a major computational task, due to the enormous search space. A possible solution is to employ deep learning strategies for genomic prediction, but the lack of explainability derived from the black-box nature of neural networks is a challenge yet to be addressed. Herein, a novel, flexible, portable, and scalable framework for network interpretatio

SUBMITTER: Graca M 

PROVIDER: S-EPMC11199512 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature