Weimiao Wu

This study introduces RVMMAT, a method for detecting time-varying genetic effects on longitudinal binary traits, and applies it to identify hypertension-associated loci.

iDESC identifies differential expression in scRNA-seq data with multiple subjects by separating subject effects from disease effects, showing better performance than existing methods.

G2S3 improves single-cell RNA sequencing data by imputing dropouts using a gene graph, enhancing expression recovery and analysis.

This study introduces L-BRAT and RGMMAT for analyzing longitudinal binary traits, identifies loci and pathways related to cocaine use, and replicates findings in an independent GWAS.