Joshua J. Joseph, Xiaofei Zhou, Mihail Zilbermint, Constantine A. Stratakis,, Fabio R. Faucz, Maya B. Lodish, Annabel Berthon, James G. Wilson, Willa A. Hsueh, Sherita H. Golden, and Shili Lin (2020) The Association of ARMC5 with the Renin-Angiotensin-Aldosterone System, Blood Pressure and Glycemia in African Americans. Supplementary Materials
Hansen, K., Siegmund, K., Lin, S. (2019) Chapter 33: DNA Methylation, 933-948. In: Handbook of Statistical Genomics (4th Edition). Ed: David Balding, Ida Moltke, and John Marioni. John Wiley & Sons.
Shokoohi, F., Khalili, A., Asgharian, M., and Lin, S. (2019) Capturing heterogeneity of covariate effects in hidden subpopulations in the presence of censoring and large number of covariates. Annals of Applied Statistics, 13, 444-465.
Zhang, F., Khalili,A., and Lin, S. (2019) Imprinting and Maternal Effect Detection Using Partial Likelihood Based on Discordant Sibpair Data. Statistica Sinica, 29, 1915-1937.
Datta, A., Biswas, S., and Lin S. (2019) A Family-Based Rare Haplotype Association Method for Quantitative Traits. Human Heredity, 83:175-195.
Park, J. and Lin, S. (2019) Evaluation and Comparison of Methods for Recapitulation of 3D Spatial Chromatin Structures. Brie ngs in Bioinformatics, 20, 1205-1214.
Han, C., Tang, H., Lou, S., Goa, Y. Cho, M. H., Lin, S. (2018) Evaluation of Recent Statistical Methods for Detecting Di erential Methylation Using BS-seq Data. OBM Genetics, 2 Article 041
Li, L., Wang, C., Lu, T., Lin, S., and Hu Y-Q. (2018) Indirect e ect inference and application to GAW 20 data. BMC Genetics, 19(Suppl 1): 67
Park, J. and Lin, S. (2018) Detection of Differentially Methylated Regions Using Bayesian Curve Credible Bands. Statistics in Biosciences, 10, 20-40.
Turkmen, A. and Lin, S. (2017) Are Rare Variants Really Independent? Genetic Epidemiology, 41, 363-371.
Park, J., Lin, S. (2017) A Random Effect Model for Reconstruction of Spatial Chro- matin Structure. Biometrics, 73, 52-62.