GenHap: Advancing Genomics and Precision Medicine with Scalable Haplotype-based Computational Methods
Genomics-driven precision medicine has the potential to revolutionize global health by predicting disease risk and uncovering underlying causes of complex diseases. To ensure that predictions are accessible, accurate and effective for people from diverse backgrounds, we need to develop innovative computational methods for genomics. The goal is to create tools that can analyze large amounts of genetic data to identify new patterns and connections to help us predict and prevent diseases. By focusing on the most prevalent diseases today, such as cardiometabolic diseases, this project intends to make a meaningful difference in public health. This work combines state-of-the-art techniques to make sense of complex genetic data using haplotype information. This involves developing methods to accurately identify the ancestral backgrounds of individuals, identify genetic risk factors for diseases, and predict disease outcomes based on combined large-scale genetic and health data.