Transcriptome‐Wide Association Studies (TWAS): Methodologies, Applications, and Challenges
Patrick Evans, Taylor Nagai, Anuar Konkashbaev, Dan Zhou, Ela W. Knapik, Eric R. Gamazon
Abstract
Transcriptome-wide association study (TWAS) methodologies aim to identify genetic effects on phenotypes through the mediation of gene transcription. In TWAS, in silico models of gene expression are trained as functions of genetic variants and then applied to genome-wide association study (GWAS) data. This post-GWAS analysis identifies gene-trait associations with high interpretability, enabling follow-up functional genomics studies and the development of genetics-anchored resources. We provide an overview of commonly used TWAS approaches, their advantages and limitations, and some widely used applications. © 2024 Wiley Periodicals LLC.
Topics & Concepts
Genome-wide association studyComputational biologyGenetic associationInterpretabilityGenomicsTranscriptomeBiologyIn silicoGeneGenomeGeneticsComputer scienceGene expressionSingle-nucleotide polymorphismMachine learningGenotypeGenetic Associations and EpidemiologyGenetic Syndromes and ImprintingBioinformatics and Genomic Networks