本课题组招收硕士和博士研究生，招生需求如下：1. 有志于做学术研究（对于硕士）；2. 对由应用问题驱动的统计方法和理论感兴趣；3. 具有较好的数学或数理统计基础；4. 熟练掌握R或python编程语言。欢迎感兴趣的同学与我联系，将个人简历和成绩单发送至yaowuliu615@gmail.com。
Liu, Y., Liu, Z., and Lin, X. (2023+) Ensemble methods for testing a global null. Journal of the Royal Statistical Society: Series B (Statistical Methodology) . In press. [link][arxiv][package]
Liu, Y., Li, Z., and Lin, X. (2022) A Minimax Optimal Ridge-Type Set Test for Global Hypothesis with Applications in Whole Genome Sequencing Association Studies. Journal of the American Statistical Association. 117(538), 897-908. [link][package]
Li, Z., Liu, Y., and Lin, X. (2022) Simultaneous Detection of Signal Regions Using Quadratic Scan Statistics With Applications in Whole Genome Association Studies. Journal of the American Statistical Association. 117(538), 823-934. [link][arxiv]
Liu, Y. and Xie, J.(2020). Cauchy combination test: a powerful test with analytic p-value calculation under arbitrary dependency structures. Journal of the American Statistical Association. 115(529), 393-402. [link][arxiv][package]
Liu, Y. and Xie, J.(2019). Accurate and efficient p-value calculation via Gaussian approximation: a novel Monte-Carlo method. Journal of the American Statistical Association. 114(525), 384-392. [link]
Liu, Y. and Xie, J.(2018). Powerful test based on conditional effects for genome-wide screening. The Annals of Applied Statistics. 12(1), 567. [link]
Li, X., Quick, C., Zhou, H., Gaynor, S., Liu, Y., Chen, H., …, Li, Z., Lin, X. (2023). Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole-genome sequencing studies. Nature Genetics, 55, 155-164. [link]
Li, Z., Li, X., Zhou, H., Gaynor, S.M., Selvaraj, M., Arapoglou, T., Quick, C., Liu, Y., Chen, H., …, Lin, X. (2022). A framework for detecting noncoding rare variant associations of large-scale whole-genome sequencing studies. Nature Methods, 19, 1599–1611. [link]
Li, X., Yung, G., Zhou, H., Sun, R., Li, Z., Liu, Y., Ionita-Laza,I., Lin, X. (2022). A Multi-dimensional Integrative Scoring Framework for Predicting Functional Regions in the Human Genome. The American Journal of Human Genetics. 109(3), 446-456. [link]
Liu, Y., Zhang, X., Lee, J., Smelser, D., Cade, B., Chen, H., Zhou, H., Kirchner, H.L., Lin, X., Mukherjee, S., Hillman, D., Liu, C., Redline, S. and, Sofer, T. (2021). Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity. International Journal of Obesity. 45, 1532-1541. [link]
Li, X., Li, Z., Zhou, H., Gaynor, S.M., Liu, Y., Chen, H.,…, and Lin, X. (2020). Dynamic incorporation of multiple in-silico functional annotations empowers rare variant association analysis of large whole genome sequencing studies at scale. Nature Genetics. 52, 969–983. [link]
Liu, Y., Chen, S., Li, Z., Morrison, A.C., Boerwinkle, E., and Lin, X. (2019). ACAT: a fast and powerful p-value combination method for rare-variant analysis in sequencing studies. The American Journal of Human Genetics. 104(3), 410-421. [link][package]
Li, Z., Li, X., Liu, Y., Shen, J., Chen, H., Zhou, H., Morrison, A.C., Boerwinkle, E., and Lin, X. (2019). Dynamic scan procedure for detecting rare-variant association regions in whole genome sequencing studies. The American Journal of Human Genetics. 104(5), 802-814. [link]
