New Techniques to Combine Measures of Statistical Significance from Heterogeneous Data Sources with Application to Analysis of Genomic Data
National Science Foundation
This project is motivated by integrative analysis of large-scale genomic data, where an important question is how to effectively combine statistical significances, or p-values, from heterogeneous data sources. Despite recent advances in theoretical and applied studies, statistical and computational challenges remain in addressing critical data features, such as complex correlations, discreteness of data, and availability of prior knowledge that could have been utilized to boost signal detection. This project will develop novel statistical methods to address the challenges and increase the statistical power for detecting valid signals. The research will facilitate innovations in statistical theory and methodology as well as in broad applications. The research activities will leverage project-oriented education, promote multi-disciplinary interactions, and benefit STEM education for the next generation of engineers and scientists, especially members of minorities underrepresented in the statistics field.
For more information, please see: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2113570&HistoricalAward...
Award Period: August 2021 - July 2024 Award Amount: $200,000