PhenoEncoder: A Discriminative Embedding Approach to Genomic Data Compression

Exploring the heritability of complex genetic traits requires methods that can handle the genome's vast scale and the intricate relationships among genetic markers. Widely accepted association studies overlook non-linear effects (epistasis), prompting the adoption of deep neural networks (DNNs)...

Full description

Saved in:

Bibliographic Details
Published in:	bioRxiv
Main Authors:	Tas, Gizem, Postma, Eric, Balvert, Marleen, Schoenhuth, Alexander
Format:	Paper
Language:	English
Published:	Cold Spring Harbor Cold Spring Harbor Laboratory Press 10.12.2024 Cold Spring Harbor Laboratory
Edition:	1.1
Subjects:	Compression Data compression Datasets Embedding Epistasis Genetic diversity Genetic markers Genomes Genomics Genotype & phenotype Haplotypes Heritability Linkage disequilibrium Neural networks Phenotypes Phenotypic variations Single-nucleotide polymorphism Autoencoder Discriminative Embedding Genomic Feature Extraction
ISSN:	2692-8205, 2692-8205
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!