Computationally Scalable Approaches for Inference in Genetics and Genomics

Explore computationally scalable methodologies for genetic and genomic inference in this 34-minute conference talk from the Computational Genomics Summer Institute. Discover advanced approaches for multi-ancestry fine-mapping that identify cis-regulatory variants underlying molecular traits and disease risk, and learn about efficient count-based models that enhance power and robustness for large-scale single-cell eQTL mapping. Examine cutting-edge computational techniques designed to handle the increasing scale and complexity of modern genomic datasets, with insights into how these methods improve the accuracy and efficiency of genetic association studies and molecular trait mapping across diverse populations.