TWAS atlas 2.0: an updated data resource for transcriptome-wide association studies.

Abstract

Transcriptome-wide association studies (TWAS), which combine large-scale GWAS and expression quantitative trait loci (eQTL) datasets to predict gene expression levels and identify trait-related genes, have recently been applied across many traits. TWAS Atlas is a comprehensive public resource that carefully curates TWAS results from a standard set of literature, helping researchers integrate and analyze numerous gene-trait associations. In TWAS Atlas 2.0 (https://ngdc.cncb.ac.cn/twas/), we not only include the latest high-quality TWAS findings but also incorporate GWAS datasets for performing TWAS analysis to expand the range of covered phenotypes, increasing gene-trait associations from 401 226 to 676 198, involving 590 traits and 24 870 genes. The knowledge graph has been significantly enhanced and enriched through information extraction from literature, now featuring new capabilities that greatly improve its usability and analytical power. We have developed multidimensional interactive analysis modules, including functional enrichment, Mendelian randomization, colocalization, and fine-mapping, providing researchers with comprehensive tools to explore causal relationships between genes and traits. These updates significantly enhance the utility of TWAS Atlas 2.0, facilitating a deeper understanding of gene expression and its regulation of complex traits.