Multi-context genetic modeling of transcriptional regulation resolves novel disease loci.

ABSTRACT: A majority of the variants identified in genome-wide association studies fall in non-coding regions of the genome, indicating their mechanism of impact is mediated via gene expression. Leveraging this hypothesis, transcriptome-wide association studies (TWAS) have assisted in both the interpretation and discovery of additional genes associated with complex traits. However, existing methods for conducting TWAS do not take full advantage of the intra-individual correlation inherently present in multi-context expression studies and do not properly adjust for multiple testing across contexts. We introduce CONTENT-a computationally efficient method with proper cross-context false discovery correction that leverages correlation structure across contexts to improve power and generate context-speci

SUBMITTER: Thompson M 

PROVIDER: S-EPMC9519579 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature