Chong Wu

Portrait of Chong Wu 

Chong Wu

Assistant Professor
Department of Statistics
Florida State University

Research interest: high-dimensional data, statistical genetics, integrative analysis, big data, and machine learning

Curriculum Vitae (July, 2019)


Google Scholar

Short Bio

Currently, I am an Assistant Professor in the Department of Statistics at Florida State University. Prior to FSU, I was a biostatistics Ph.D. student at the University of Minnesota, co-advised by Profs. Weihua Guan and Wei Pan. I received my bachelor's degree in Applied Math from the Huazhong University of Science and Technology in 2013.

My research interests are in statistical genetics and genomics, statistical learning, and machine learning. In the past a few years, I have obtained a diverse training in developing statistical methods and algorithm for analyzing multiple types of genetic and genomic data, including genome-wide association study (GWAS) data, DNA methylation data, and human microbiome data. My work includes gene- and pathway-based association testing and a new algorithm for clustering. To practice and facilitate reproducible research, I have developed and currently maintain several software and their online manuals (see Software page). My recent work involves integrative analysis of GWAS with multiple sources of omics data.

If you have some massive and messy genetics and genomics data and need to find a biostatistician to analyze your data, please do not hesitate to contact me.

I am seeking two highly self-motivated students to join my research group. If you are interested, feel free to email me or stop by my office.

Selected Publications [by topic]

* Corresponding author

  1. Wu, C.* and Pan, W.* (2019)
    Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes. Accepted by Bioinformatics.

  2. Wu, C.*, Xu, G., and Pan, W.* (2019).
    An adaptive test on high dimensional parameters in generalized linear models. Accepted by Statistica Sinica.

  3. Wu, C. and Pan, W. (2018).
    Integrating eQTL data with GWAS summary statistics in pathwaybased analysis. Genetic Epidemiology, 42.3: 303-316.
    (This paper won a poster talk at ASHG 2017 Annual Meeting.)

  4. Xu, Z., Wu, C., Wei, P., and Pan, W. (2017+).
    A powerful framework for integrating eQTL and GWAS summary data. Genetics, 207(3), 893-902.

  5. Liu, B., Wu, C., Shen, X., and Pan, W. (2017).
    A novel and efficient algorithm for de novo discovery of mutated driver pathways. Annals of Applied Statistics, 17(3):1481-1512.

  6. Xu, Z., Wu, C., Pan, W., and ADNI. (2017).
    Imaging-wide association study: integrating imaging endophenotypes in GWAS. NeuroImage, 159:159-169.
    (This paper won a platform presentation at the American Society of Human Genetics (ASHG) 2017 Annual Meeting.)

  7. Wu, C., Kwon, S., Shen, X., and Pan, W. (2016).
    A new algorithm and theory for penalized regression-based clustering. Journal of Machine Learning Research, 17(18):1-25 (Co-first author).

  8. Wu, C., Chen, J., Kim, J., and Pan, W. (2016).
    An adaptive association test for microbiome data. Genome Medicine, 8(1):1-12.
    (This paper won the 2016 JSM Distinguished Student Paper Award on Statistics in Genomics and Genetics Section)

  9. Wu, C., Demerath, E. W., Pankow, J. S., Bressler, J., Fornage, M., Grove, M. L., Chen, W., and Guan, W. (2016).
    Imputation of missing covariate values in epigenome-wide analysis of DNA methylation data. Epigenetics, 11(2):132-139.
    (The official journal of the DNA Methylation Society.)

Selected Software

  • prclust: Penalized Regression-Based Clustering Methods;

  • MiSPU: Microbiome Based Sum of Powered Score (MiSPU) Tests;

  • GLMaSPU: Adaptive Tests on High Dimensional Parameters in Generalized Linear Models;

  • IWAS: Imaging-Wide Association Study;

  • TWAS: Integrating eQTL and GWAS data;

  • aSPUpath2: Integrating eQTL data with GWAS summary statistics in pathway-based analysis.


For me, teaching can be described as a rewarding and fulfilling experience. I am the instructor for the following courses.

Selected Presentations

I enjoy sharing ideas and presenting my works. I usually attend JSM, ENAR, and ASHG each year.


  • ENAR Distinguished Student Paper Award, 2019

  • James R. Boen Student Achievement Award, Division of Biostatistics, University of Minnesota, 2018

  • Pre-Doctoral Trainee Award, Association of Chinese Geneticists in America (ACGA), 2017

  • Elected to Delta Omega (Public Health Honorary Society), 2017

  • Elected to Simga Xi (The Scientific Research Society), 2017

  • JSM Distinguished Student Paper Award on Statistics in Genomics and Genetics Section, 2016

  • Doctoral Dissertation Fellowship, University of Minnesota, 2016

  • Travel Award, Computational Neuroscience Summer School, Statistical and Applied Mathematical Sciences Institute, 2015

  • Dean's Ph.D. Scholarship, University of Minnesota, 2013

  • Honorable Mention in Mathematical Contest in Modeling, Consortium for Mathematics and Its Application, 2012

  • National Scholarship, Ministry of Education, China, 2011


Chong Wu
201C OSB, 117 N. Woodward Ave.
P.O. Box 3064330, Tallahassee, FL, 32306-4330