Dr. Kai Yu's research addresses a wide variety of statistically and computationally challenging problems that have arisen in design and analysis of modern high-dimensional genetic and molecular epidemiologic studies, including:
- Statistical methods for genetic and genomic studies
- Tree-based models and applications in molecular epidemiology studies
- Integrative analysis using individual-level and summary-level data
- Extremely small P-value Evaluation for Resampling-based Test (EXPERT)
- Bayesian model for Detecting Gene Environment interaction (BaDGE)
- Bayesian Subset Regression (BSR)
- Summary statistics-based genetic pathway analysis software (ARTP2)
- Generalized Integration Model for combining summary statistics with individual-level data (GIM)
Dr. Yu received a Ph.D. in biostatistics from the University of Pittsburgh in 2000, and had postdoctoral training in statistical genetics at Stanford University. He joined NCI in 2005 as a tenure-track investigator, and was awarded scientific tenure by the NIH and appointed senior investigator in 2012. In 2009, he received an NIH Merit Award for developing creative statistical methods for genetic epidemiologic studies. He is an elected Fellow of the American Statistical Association.
- Li D, Duell EJ, Yu K, Risch HA, Olson SH, Kooperberg C, Wolpin BM, Jiao L, Dong X, Wheeler B, Arslan AA, Bueno-de-Mesquita HB, Fuchs CS, Gallinger S, Gross M, Hartge P, Hoover RN, Holly EA, Jacobs EJ, Klein AP, LaCroix A, Mandelson MT, Petersen G, Zheng W, Agalliu I, Albanes D, Boutron-Ruault MC, Bracci PM, Buring JE, Canzian F, Chang K, Chanock SJ, Cotterchio M, Gaziano JM, Giovannucci EL, Goggins M, Hallmans G, Hankinson SE, Hoffman Bolton JA, Hunter DJ, Hutchinson A, Jacobs KB, Jenab M, Khaw KT, Kraft P, Krogh V, Kurtz RC, McWilliams RR, Mendelsohn JB, Patel AV, Rabe KG, Riboli E, Shu XO, Tjønneland A, Tobias GS, Trichopoulos D, Virtamo J, Visvanathan K, Watters J, Yu H, Zeleniuch-Jacquotte A, Amundadottir L, Stolzenberg-Solomon RZ. Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer. Carcinogenesis. 2012;33(7):1384-90.
- Yu K, Wacholder S, Wheeler W, Wang Z, Caporaso N, Landi MT, Liang F. A flexible Bayesian model for studying gene-environment interaction. PLoS Genet. 2012;8(1):e1002482.
- Zhang H, Shi J, Liang F, Wheeler W, Stolzenberg-Solomon R, Yu K. A fast multilocus test with adaptive SNP selection for large-scale genetic-association studies. Eur J Hum Genet. 2014;22(5):696-702.
- Yu K, Zhang H, Wheeler W, Horne HN, Chen J, Figueroa JD. A robust association test for detecting genetic variants with heterogeneous effects. Biostatistics. 2015;16(1):5-16.
Related Scientific Focus Areas
Genetics and Genomics
This page was last updated on Friday, April 29, 2022