Disentangling associations between complex traits and cell types with <i>seismic</i>.

ABSTRACT: Integrating single-cell RNA sequencing (scRNA-seq) with Genome-Wide Association Studies (GWAS) can help reveal GWAS-associated cell types, furthering our understanding of the cell-type-specific biological processes underlying complex traits and disease. However, current methods have technical limitations that hinder them from making systematic, scalable, interpretable disease-cell-type associations. In order to rapidly and accurately pinpoint associations, we develop a novel framework, seismic, which characterizes cell types using a new specificity score. We compare seismic with alternative methods across over 1,000 cell type characterizations at different granularities and 28 traits, demonstrating that seismic both corroborates findings and identifies trait-relevant c

SUBMITTER: Lai Q 

PROVIDER: S-EPMC11100625 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature