Professor of Biostatistics
Dr. Lin’s research interests lie in statistical genetics and genomics. She is interested in development and application of statistical and computational methods for analysis of high-throughput genetic, genomic and ‘omics data in epidemiological, environmental and clinical sciences, especially genetic and epigenetic epidemiology, genes and environment, and medical genomics. Current research projects include genome-wide array association studies, whole genome sequencing association studies, gene-environment interactions, and genome-wide DNA methylation studies, pathway and network analysis, and integrative genetics and genomics. She currently serves as the coordinating director of the Program of Quantitative Genomics of Harvard School of Public Heath http://www.hsph.harvard.edu/pqg. Her methodological work is currently supported by the MERIT award from the National Cancer Institute on “Statistical Methods for Correlated and High-Dimensional Biomedical Data,” and the PO1 from the National Cancer Institute on “Statistical Informatics in Cancer Research.” She is the contacting PI for the training grant entitled Joint training in biostatistics and computational biology.
Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M. and Lin, X (2011) Rare Variant
Association Testing for Sequencing Data Using the Sequence Kernel Association Test (SKAT). American Journal of Human Genetics, 89, 82-93.
Huang, Y. T., Lin, X., Liu, Y., Chirieac,L. R., McGovern, R., Wain, J. C., Heist,
R. S, Skaug, V., Zienolddiny, S., Haugen, A., Su, L., Fox, E. D., Wong, K. K., and
David C. Christiani (2011) Cigarette Smoking Increases Copy Number Alterations
in Non-Small Cell Lung Cancer, Proceedings of the National Academy of Sciences,
108:16345-16350. doi: 10.1073/pnas.1102769108
Wang, L, Rotnizky, A., Lin, X., Millikan, R., and Thall, P. (2012) Evaluation of
Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer (with discussions). Journal of American Statistical Association, 107, 493-508.
Lin, X., Li, L., Christiani, D. C., and Lin, X. (2013) Test for the Interaction between
a Genetic Marker Set and Environment in Generalized Linear Models. Biostatistics,
Lee, S., Teslovich, T.M., Boehnke, M. and Lin, X. (2013) General framework for
meta-analysis of rare variants in sequencing association studies. American Journal of Human Genetics, 93, 42-53.
Huang. Y. T., VanderWeele, T. J., and Lin, X. (2014) Joint Analysis of SNP and
Gene Expression Data in Genetic Association Studies of Complex Diseases. Annals
of Applied Statistics, in press.