Predicting the genetic component of gene expression using gene regulatory networks.

ABSTRACT:

Motivation

Gene expression prediction plays a vital role in transcriptome-wide association studies. Traditional models rely on genetic variants in close genomic proximity to the gene of interest to predict the genetic component of gene expression. Here, we propose a novel approach incorporating distal genetic variants acting through gene regulatory networks, in line with the omnigenic model of complex traits.

Results

Using causal and coexpression Bayesian networks reconstructed from genomic and transcriptomic data, inference of gene expression from genotypic data is achieved through a two-step process. Initially, the expression level of each gene is predicted using its local genetic variants. The residual differences between the observed and predicted expression levels are t

SUBMITTER: Mohammad GI 

PROVIDER: S-EPMC11665636 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature