Seunggeun Shawn Lee, PhD
- Adjunct Professor of Biostatistics
- BIOSTAT651: Applied Statistics II: Extensions for Linear Regression Syllabus (PDF)
- B.S., Biology and Statistics, Seoul National University, 2005
- PhD, Biostatistics, University of North Carolina, 2010
Dutta D, Scott L, Boehnke M, Lee S (2019). Multi‐SKAT: General framework to test for rare‐variant association with multiple phenotypes. Genetic Epidemiology 43(1), 4-23
Zhou W, Nielsen J, Fritsche L, Dey R, Gabrielsen M, Wolford B, LeFaive J, VandeHaar P, Gagliano S, Gifford A, Bastarache L, Wei WQ, Denny J, Lin M, Hveem K, Kang HM, Abecasis G, Willer C#, Lee S# (2018) Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nature Genetics 50, 1335-1341
# equal contribution
Dey R, Schmidt E, Abecasis G, Lee S (2017) A fast and accurate algorithm to test for binary phenotypes and its application
to PheWAS. American Journal of Human Genetics, 101, 37-49.
He Z, Lee S, Zhang M, Smith J, Guo X, Palmas W, Kardia S, Ionita‐Laza I, Mukherjee B (2017).
Rare‐variant association tests in longitudinal studies, with an application to the
Multi‐Ethnic Study of Atherosclerosis (MESA). Genetic Epidemiology 41(8):801-810.
He Z, Zhang M, Lee S, Smith J, Kardia S, Roux V, Mukherjee B (2017). Set-Based Tests for the Gene–Environment
Interaction in Longitudinal Studies. Journal of the American Statistical Association 101, 340-352.
Lee S, Kim S, Fuchsberger C (2017). Improving power for rare‐variant tests by integrating external controls. Genetic Epidemiology 41(7): 610-619.
Lee S, Sun W, Wright F, Zou F (2017). An improved and explicit surrogate variable analysis procedure by coefficient adjustment. Biometrika 104(2): 303-316.