Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms.

ABSTRACT: Genes act in concert with each other in specific contexts to perform their functions. Determining how these genes influence complex traits requires a mechanistic understanding of expression regulation across different conditions. It has been shown that this insight is critical for developing new therapies. Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Here we introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis. This representation is based on mod

SUBMITTER: Pividori M 

PROVIDER: S-EPMC10492839 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature