Methods development for gene-environment interaction analysis on cloud platforms
Approved Research ID: 92681
Approval date: December 14th 2022
Gene-environment interactions (GEI) play an important role in understanding the origins and causes of complex diseases. By studying these interactions, researchers have been able to more accurately assess the influence of environmental and genetic components. The understanding of GEI has important implications for how we prevent and treat disease as well as predict disease rates.
Currently available software programs do not fulfill the needs of the GEI research community. With advances in technology, the genetic data used in GEI studies are being generated on a very large scale. However, the tools developed to analyze these data were not optimized for handling such large sample sizes. This 2 year project will develop efficient statistical methods and computational algorithms to meet the analytical needs of current and future large-scale GEI studies. Using the UK Biobank dataset, we propose testing and implementing these methods and algorithms in an open source software and cloud-based analysis pipeline and to facilitate GEI research on complex cardio-metabolic, lung, blood and sleep diseases and related conditions using hundreds of thousands to millions of samples. The information from UK Biobank data will be used in evaluating the performance of our software tools in simulations and real data applications.