yicheng tao

Abstract Single-cell multi-omics technologies capture complementary molecular layers, enabling a comprehensive view of cellular states and functions. However, integrating these data types poses significant challenges when their features are weakly linked and cell population sizes are imbalanced. Currently, no method efficiently addresses these two issues simultaneously. Therefore, we developed CelLink, a novel single-cell multi-omics data integration method designed to overcome these challenges.

Abstract Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3,4,5.