Chao Xu, Ph.D.


Assistant Professor of Biostatistics and Epidemiology

Phone: (405) 271-2229, ext 48054

The University of Oklahoma Health Sciences Center
801 Northeast 13th Street, Room 321
Post Office Box 26901
Oklahoma City, Oklahoma 73190




Education and Training:

  • Ph.D. in Biostatistics, Tulane University, New Orleans, USA May 2018
  • M.ENG. in Systems Engineering, University of Shanghai for Science and Technology, China Jun 2011
  • B.S. in Management Information System, Jiangsu University of Science and Technology, China Jun 2008
  • Summer Institute in Statistical Genetics, University of Washington, Seattle, USA, 2010 and 2013


Appointments and Positions:

  • Assistant Professor, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, 2018-Present

Complete List of Publications:

Most Recent 5 Publications:

  • Xu C*, Fang J*, Shen H, Wang YP, Deng HW. EPS-LASSO: Test for High-Dimensional Regression Under Extreme Phenotype Sampling of Continuous Traits. Bioinformatics, 2018, 34 (12), 1996-2003
  • Xu C, Wu K, Zhang J, et al. Low-, high-coverage and two-stage sequencing in the design of the genetic association study. Genetic Epidemiology, 2017, 41(3): 187-197
  • Xu C*, Zhang J*, Lin D, et al. A Systemic Network Analysis of Transcriptomic and Epigenomic Data to Reveal Regulation Patterns for Complex Disease. G3: Genes, Genomes, Genetics, 2017, 7(7): 2271-2279 
  • Xu C, Zhang J, Wang YP, Deng HW, Li J. Characterization of human chromosomal material exchange with regard to the chromosome translocations using next-generation sequencing data. Genome Biology and Evolution, 2014, 6(11), 3015-3024
  • Fang J, Xu C, Zille P, et al. Fast and Accurate Detection of Complex Multi-Modal Imaging Genetics Associations based on Greedy Projected Distance Correlation. IEEE Transactions on Medical Imaging, 2017, (99)


Research Interests:

  • Statistical Genetics, High-dimensional Statistics, Bioinformatics, Genetic Epidemiology.

Current Major Research Projects:

  • Research design and data analysis in neurology and cancer study.
  • Statistical method development for genetic study.