Efficient Count-Based Models Improve Power and Robustness for Large-Scale Single-Cell eQTL Mapping

Learn about efficient count-based models that enhance power and robustness for large-scale single-cell expression quantitative trait loci (eQTL) mapping in this 28-minute conference talk from the Computational Genomics Summer Institute. Explore how these advanced statistical models address challenges in single-cell genomics analysis, particularly in identifying genetic variants that influence gene expression at the cellular level. Discover methodological improvements for multi-ancestry fine-mapping of cis-regulatory variants and their applications in understanding molecular traits and disease risk. Gain insights into cutting-edge computational approaches that improve the detection and characterization of genetic regulatory mechanisms in single-cell datasets, with practical implications for genomics research and precision medicine applications.