Xihong Lin

Professor of Biostatistics

Department of Biostatistics

Xihong Lin’s Group Website  |  Program in Quantitative Genomics’ Website

Bio

Xihong Lin is Professor and former Chair of the Department of Biostatistics, Coordinating Director of the Program in Quantitative Genomics at the Harvard T. H. Chan School of Public Health, and Professor of the Department of Statistics at the Faculty of Arts and Sciences of Harvard University, and Associate Member of the Broad Institute of Harvard and MIT.

Dr. Lin is an elected member of the National Academy of Medicine. She received the 2002 Mortimer Spiegelman Award from the American Public Health Association, and the 2006 Committee of Presidents of Statistical Societies (COPSS) Presidents’ Award and the 2017 COPSS FN David Award. She is an elected fellow of American Statistical Association (ASA), Institute of Mathematical Statistics, and International Statistical Institute.

Dr. Lin’s research interests lie in development and application of statistical and computational methods for analysis of massive data from genome, exposome and phenome, and scalable statistical inference and learning for big genomic, epidemiological and health data.  Examples include analytic methods and applications for large scale Whole Genome Sequencing studies, biobanks and electronic health records, whole genome variant functional annotations, genes and environment, multiple phenotype analysis, risk prediction, integrative analysis of different types of data, causal mediation analysis and causal inference, analysis of epidemiological and complex observational study data. Her theoretical and computational statistical research includes statistical methods for testing a large number of complex hypotheses, causal inference,  statistical inference for large covariance matrices, prediction models using high-dimensional data, cloud-based statistical computing, and statistical methods for epidemiological studies.

Dr. Lin’s statistical methodological research has been supported by the MERIT Award (R37) (2007-2015) and the Outstanding Investigator Award (OIA) (R35) (2015-2022) from the National Cancer Institute (NCI). She is the contact PI of the Harvard Analysis Center of the Genome Sequencing Program of the National Human Genome Research Institute, and the multiple PI of the U19 grant on Integrative Analysis of Lung Cancer Etiology and Risk from NCI. She is also the contact PI of the T32 training grant on interdisciplinary training in statistical genetics and computational biology.  She is the former contact PI of the Program Project (PO1) on Statistical Informatics in Cancer Research from NCI.

Dr. Lin is the former Chair of the COPSS (2010-2012) and a former member of the Committee of Applied and Theoretical Statistics (CATS) of the National Academy of Science. She co-launched the new Section of Statistical Genetics and Genomics of the American Statistical Association and served as a former section chair. She is the former Coordinating Editor of Biometrics and the founding co-editor of Statistics in Biosciences.  She has served on a large number of committees of many statistical societies, and numerous NIH and NSF review panels.

Selected Publications

[Full list of PubMed articles]

  • Li, X., Li, Z., Zhou, H, Gaynor, S, …, Rotter, J., Willer, C. J., Peloso, G. M., Natarajan, P., 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, in press.

  • Pan, A., Liu, L., Wang, C., Guo, H., Hao, X., Wang Q., Huang, J., He, N., Yu, Ho, Lin, X., Wei, S., Wu, T. (2020) Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China. Journal of the American Medical Association, doi:10.1001/jama.2020.6130

  • Segal, E., Zhang, F., Lin, X., King, G., Shalem, O, …,  Steinherz, R., Stevens, I., Vilo, J., Wilmes, P.,  Altae-Tran, H. (2020). Building an International Consortium for Tracking Coronavirus Health Status, Nature Medicine, in press

  • Liu, Z., Barnett, I, and Lin, X. (2020) Differences in principal component methods between multiple phenotype regression and multiple SNP regression in genetic association studies. Annals of Applied Statistics, in press.

  • Sun, R. and Lin, X. (2019).   Generalized Berk-Jones Statistic for SNP-Set Tests in GWAS.  Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2019.1660170

  • Xu, M., Yao, Y., Chen, H., Zhang, S., Cao, S., Zhang, Z., Luo, B., Liu, Z., Li, Z., Xiang, T., H, G., Feng, Q., Chen, L., Guo, X., Jia, W., Chen, M., Zhang, X., Xie, S., Peng, R., Peng, R., Chang, E, Pedergnana, V., Feng, L., Bei, J., Xu, R., Zeng, M., Ye, W., Adami, H. O., Lin, X., Zhai, W., Zeng, Y. X., Liu, J. (2019).  Genome sequencing analysis identifies Epstein-Barr virus subtypes associated with high risk of nasopharyngeal carcinoma, Nature Genetics, 51, 1131-1136.

  • Liu, Z. and Lin, X. (2019) A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies. Journal of the American Statistical Association, 114(527), pp.975-990.

  • Sun, R., Hui, S., Bader, G., Lin, X., and Kraft, P. (2019). Powerful Gene Set Analysis in GWAS with the Generalized Berk-Jones Statistic. Plos Genetics15(3), p.e1007530.

  • Liu, Y., Chen, S., Li, Z., Morrison, A. C., Boerwinkle, E., and Lin, X. (2019) ACAT:  Fast and Powerful P-value Combination Method for Rare-variant Analysis in Sequencing Studies. American Journal of Human Genetics, 104(3), pp.410-421.

  • 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, American Journal of Human Genetics, 104(5), pp.802-814