New Approaches for Causal Inference from Genomic Data

Explore cutting-edge methodologies for establishing causal relationships in genomic research through this 52-minute conference talk delivered at the Computational Genomics Summer Institute. Delve into innovative statistical and computational approaches that address the fundamental challenge of inferring causation rather than mere correlation from complex genomic datasets. Learn about advanced techniques that overcome traditional limitations in genomic causal inference, including methods for handling confounding variables, population stratification, and the unique challenges posed by high-dimensional genomic data. Discover how these new approaches can be applied to understand disease mechanisms, identify therapeutic targets, and unravel the causal pathways underlying complex traits and diseases. Gain insights into the theoretical foundations and practical implementations of these methods, along with their potential impact on precision medicine and genomic research.