A tissue-specific collaborative mixed model for jointly analyzing multiple tissues in transcriptome-wide association studies.

ABSTRACT: Transcriptome-wide association studies (TWASs) integrate expression quantitative trait loci (eQTLs) studies with genome-wide association studies (GWASs) to prioritize candidate target genes for complex traits. Several statistical methods have been recently proposed to improve the performance of TWASs in gene prioritization by integrating the expression regulatory information imputed from multiple tissues, and made significant achievements in improving the ability to detect gene-trait associations. Unfortunately, most existing multi-tissue methods focus on prioritization of candidate genes, and cannot directly infer the specific functional effects of candidate genes across different tissues. Here, we propose a tissue-specific collaborative mixed model (TisCoMM) for TWASs, leveraging the co-

SUBMITTER: Shi X 

PROVIDER: S-EPMC7641735 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature