Hongzhe Li (Lee), Ph.D.

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Professor of Biostatistics in Biostatistics and Epidemiology
Department: Biostatistics and Epidemiology

Contact information
Department of Biostatistics and Epidemiology
University of Pennsylvania Perelman School of Medicine
215 Blockley Hall
423 Guardian Drive
Philadelphia, PA 19104-6021
Office: 215-573-5038
Fax: 215-573 1050
Education:
B.S. (Mathematics/Information)
Peking University, 1989.
Ph.D. (Statistics)
University of Washington, 1995.
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Description of Research Expertise

My methods reserach was mostly motivated by problems in genetics and genoimics. I have worked on a variety problems in statistical genetics and genomics, including methods for family-based genetic linkage and association analysis, methods for admixture mapping, methods for genome-wide association analysis, methods for analysis of microarray time course gene expression data, high dimensional regression analysis for genomic data, methods for copy number variation analysis and methods for analysis of next generation sequence data. I have published both statistical methodological research in top statistics/biostatistics journals (JASA, AOS, AOAS, Biometrika, Biometrics, Biostatistics etc ) and in top genetics journals (AJHG, Plos Genetics, etc) and collaborative research in top scientific journals (Science, NEJM, Nature, Nature Genetics, PNAS, Developmental Cell etc).

Selected Publications

Cai TT, Li H, Ma J, Xia Y: Differential Markov Random Field Analysis with an Application to Detecting Differential Microbial Community Networks. Biometrika 2019, in press.

Cao Y, Zhang A, Li H : Multi-sample estimation of bacterial composition matrix in metagenomics data. Biometrika 2019, accepted.

Cao Y, Lin W, Li H: Large covariance estimation for compositional data via composition-adjusted thresholding. Journal of the American Statistical Association 2019, accepted Notes: DOI: 10.1080/01621459.2018.1442340.

Gao B, Liu X, Li H, Cui Y : Integrative analysis of genetical genomics data incorporating network structures. Biometrics 2019, accepted.

Gluck C, Qiu C, Han SY, Palmer M, Oark J, Ko YA, Guan Y, Sheng X, Hanson RL, Huang J, Chen Y, Park ASD, Mantzaris I, Verma A, Li H, Susztak K: Kidney cytosine methylation changes can improve renal function decline estimation in patients with diabetic kidney disease. Nature Communications 2019, accepted.

Sohn M, Li H : Compositional mediation analysis for microbiome studies. Annals of Applied Statistics 13(1): 661-681, Mar 2019.

Guo Z, Wang W, Cai T, Li H: Optimal estimation of genetic relatedness in high-dimensional linear models. Journal of the American Statistical Association 114(525): 358-369, 2019.

Gao Y, Li H: Quantifying and comparing bacterial growth dynamics in multiple metagenomic samples. Nature Methods 15(12): 1041-1044, Dec 2018.

Friedman ES, Li Y, Shen TD, Jiang J, Chau L, Adorini L, Babakhani F, Edwards J, Shapiro D, Zhao C, Carr RM, Bittinger K, Li H, Wu GD: FXR-Dependent Modulation of the Human Small Intestinal Microbiome by the Bile Acid Derivative Obeticholic Acid Gastroenterology 155(6): 1741-1752.e5, Dec 2018 Notes: doi:10.1053/j.gastro.2018.08.022. Epub 2018 Aug 23.

Li ZG, Lee K, Karagas MR, Madan JC, Hoen AG, O'Malley AJ, Li HZ: Conditional Regression Based on a Multivariate Zero-Inflated Logistic-Normal Model for Microbiome Relative Abundance Data. Statistics in Biosciences 10(3): 587-608, Dec 2018.

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Last updated: 04/30/2019
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