PUBHL Biostatistics Division
School of Public Health
Twin Cities
School of Public Health
Twin Cities
Project Title:
Statistical Methods for Prediction and Causal Inference Using Genome-Wide Association Studies
These researchers use powerful statistical approaches for heritability estimation, estimating genetic correlation and performing prediction and Mendelian Randomization using genome-wide data on families and unrelated individuals. Their approaches will provide insights into the complex interplay between genes and environmental factors in the development of a disease. The researchers will implement these approaches on a dataset from the Minnesota Center for Twin and Family Research (MCTFR), a longitudinal prospective study of families to characterize the nature of gene-environment interplay in the development of substance use disorders. The methods will also be implemented on UK Biobank datasets.
Project Investigators
Professor Saonli Basu
Monalisa Bilas
Christian Coffman
Simion De
Kody DeGolier
Dr. Lynn Eberly
Dr. Eric Feczko
Professor Nathan Pankratz
Sydney Presler
Gokul Seshadri
Hai Long Tran
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