Xuexia Wang


Department of Biostatistics

Office: 305-348-7527

Email: xuexwang@fiu.edu


Development of statistical methods and computational tools in genetic discovery and risk prediction; identification of genetic risk factors for cancer and its treatment related adverse outcomes


  • Michigan Technological University, Ph.D.
  • Capital University of Economics and Business, Ph.D
  • Shandong Normal University, B.S.


Dr. Xuexia (Helen) Wang is Professor of Biostatistics at the Florida International University (FIU). Prior to joining FIU in 2022, she worked as Associate Professor of Statistics at University of North Texas (2016 - 2022),  Assistant Professor, and then Associate Professor of Biostatistics in School of Public Health at the University of Wisconsin - Milwaukee (2011 - 2016), Assistant Research Professor at the City of Hope National Medical Center for one year, and a postdoctoral researcher at the University of Pennsylvania (UPenn), School of Medicine for one and a half years.

Dr. Wang has been successful in obtaining extramural funding with a total of $8M grants in her whole career. She have been affiliated with $938,017 of funded research as a PI, Co-PI, and subcontract PI. Dr. Wang has over 50 peer-reviewed publications in areas of economics, public health, preventive medicine, and biostatistics. These publications have been cited approximately 3000 times.

She has taught numerous graduate-level and undergraduate-level courses related to statistics, statistical genetics, computational statistics, etc. In addition, she has been the advisor of over 20 graduate and undergraduate students.

Dr. Wang’s expertise in methodology development and researching the risk factors for various diseases, and her extensive experience in teaching and supervising students in public health and biomedical science research, will further her success at FIU. She will continue these activities collaboratively with students and colleagues in the Stempel Colleg and the whole campus. She will provide her support within and outside of the department in teaching and curricular development, supervising students and research assistants, providing biostatistics consulting services, and mentoring junior faculty. She will also continue to work with her collaborators and seek more funding opportunities as primary investigator and co-investigator to support her research on methodological development in statistical genetics and applied epidemiology. Particularly, in her future research proposals, she will focus on developing and applying novel statistical approaches that address the analytic needs of geneticists, epidemiologists, and oncologists.


Dr. Wang’s lab focuses on development of novel statistical methods and computational tools in genetic discovery and risk prediction for complex diseases and idification of risk factors for cancer and its treatment-related adverse outcomes, autism, schizophrenia, and glaucoma, etc. They have developed many statistical methods and computational tools for identifying and characterizing genetic variants associated to complex diseases, especially for admixed populations. They have worked closely with collaborators in study design, power estimation, and procedures for big and complex data analysis.


Selected publications from over 50 (*corresponding author) 

  1. Cao X, Wang X, Zhang SL, Sha Q. (2022) Gene-based Association Tests Using GWAS Summary Statistics and Incorporating eQTL. Scientific Reports. 2022 Mar 3;12(1):3553. doi: 10.1038/s41598-022-07465-0.

  2. Zhang J, Guo X, Gonzales S, Yang J, Wang X*. (2020) TS: a powerful truncated test to detect novel disease associated genes using publicly available gWAS summary data. BMC Bioinformatics, 4;21(1):172.

  3. Zhang J, Xie S, Gonzales S, Liu J, Wang, X.* (2020) A fast and powerful eQTL weighted method to detect genes associated with complex trait using GWAS summary data. Genetic Epidemiology, 44(6):550-563 (This paper was selected by the Genetic Epidemiology as the journal’s highlight for the journal in the month.)

  4. Singh P, Wang X, Hageman L, Chen Y, Magdy T, et al. (2020) Association of GSTM1 null variant with anthracycline‐related cardiomyopathy after childhood cancer—A Children's Oncology Group ALTE03N1 report. Cancer, 126(17): 4051-4058.

  5. Zhang J, Wu B, Sha Q, Zhang S, Wang X.* (2019) A general statistic to test an optimally weighted combination of common and/or rare variants. Genetic Epidemiology, 43(8):966-979.

  6. Zhang J, Sha Q, Liu G, Wang X.* (2019) A gene based approach to test genetic association based on an optimally weighted combination of multiple traits. PLoS One, 14(8):e0220914.

  7. Zhang J, Sha Q, Hao H, Zhang S, Gao XR, Wang X.* (2019) Test gene-environment interactions for multiple traits in sequencing association studies Hum Hered, 84(4-5):170-196.

  8. Wang X, Sun CL, Hageman L, Smith K, Singh P, et al. (2017) Clinical and genetic risk prediction of subsequent CNS tumors in survivors of childhood cancer: A Report from the COG ALTE03N1 Study. Journal of Clinical Oncology, 35(32):3688-3696. PMCID: PMC5678343.

  9. Wang X, Xiao R, Zhu X, and Li M. (2017) Gene mapping in admixed families: a cautionary note on the interpretation of the transmission disequilibrium test and a possible solution, Human Heredity, Jan 12;81(2):106-116.

  10. Wang X, Sun CL, Quiñones-Lombraña A, Singh P, et al. (2016) CELF4 variant and Anthracycline-related Cardiomyopathy – A COG Study (ALTE03N1). J Clin Oncol. 10;34(8):863-70. doi: 10.1200/JCO.2015.63.4550.

  11. Wang X, Zhao X, and Zhou J. (2016) Testing rare variants for hypertension using family-based tests with different weighting schemes. BMC Proc, 10(Suppl 7):61; DOI

  12. Wang Z, Wang X, Sha Q. (2016) Joint analysis of multiple traits in rare variant association studies. Annual of Human Genetics, 00, 1-10.

  13. Zhu H, Wang Z, Wang X, Sha Q. (2016) A novel statistical method for rare variants association studies in general pedigrees. BMC Proc., 10(Suppl 7):22; DOI 10.1186/s12919-016-0029-6.

  14. Wang X, Zhang SL, Li Y, and Sha Q. (2015) A powerful approach to test an optimally weighted combination of rare variants in admixed populations. Genetic Epidemiology. 39:294-305. PMID:25758547.

  15. Wang X, Liu W, Sun CL, et al. (2014) Hyaluronidase synthase 3 (HAS3) variant and Anthracycline-related Cardiomyopathy – A report from the Children’s Oncology Group. Journal of Clinical Oncology. 32(7):647-53. PMID:24470002.

  16. Sha Q, Wang X, Wang XL, Zhang SL. (2012) Detecting association of rare and common variants by testing an optimally weighted combination of variants. Genetic Epidemiology, 36(6):561-571. PMID:22714994.

  17. Wang X, Zhu X, Qin H, Cooper R, Ewens W, Li C, Li M. (2011) Adjustment for local ancestry in genetic association analysis of admixed populations. Bioinformatics, 27(5):670-677.

  18. Wang X, Sha Q, Zhang SL. (2009) A new association test to test multiple-marker asso Genetic Epidemiology. 33:164-71. PMID:18720476.