Discovering disease-associated genes from whole genome sequencing datasets is challenging and current methods operate with low precision. Prof. Zheyang Wu, Professor of Mathematical Sciences and affiliated with the Bioinformatics & Computational Biology Program and the Data Science Program, was recently awarded a 3-year project from the National Science Foundation to develop new statistical tools to enhance the power and precision of discovering disease-associated genes. By integrating diverse sources of genomic information and improving how prior knowledge and statistical evidence are combined, the project aims to uncover subtle genetic signals that might otherwise be missed. It focuses on two core challenges: (1) designing more effective weighting strategies for incorporating prior information when combining statistical significances, and (2) developing new methods to integrate discrete statistics within a general hypothesis testing framework. The project will implement and apply these approaches to whole genome sequencing data analysis.
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