Chong Wu
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Chong Wu Assistant Professor Research interest: Statistical genetics/genomics, integrative analysis, big data, machine learning, causal inference, and high-dimensional inference. |
Short Bio
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 Huazhong University of Science and Technology in 2013.
My research interests are in statistical genetics and genomics, statistical learning, and machine learning. I have obtained diverse training and experiences in developing statistical methods and algorithms 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, integrative -omics analysis, new algorithms in clustering, Mendelian randomization, and polygenic risk scores. To practice and facilitate reproducible research, I have developed and currently maintain several software (most in R packages) and their online manuals. My recent work involves integrative analysis of GWAS with multiple sources of omics data.
News
2021-09: Our SUMMIT paper won a poster talk (top 10% among all posters) at ASHG 2021. Congraulations, Zichen!
2021-09: Our polygenic risk score in prostate cancer paper has been published in Cancer Communications.
2021-05: Our COVID-19 integrative analysis paper has been accepted by Genetics in Medicine.
2021-01: Our R03 proposal (Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease) has been funded by NIA.
Selected Publications [by topic]
* Corresponding author
He, Y., Xu, G., Wu, C., and Pan, W. (2021)
Asymptotically Independent U-Statistics in High-Dimensional Testing. Annals of Statistics, 49(1), 154-181.Wu, C.*, Bradley J., Li, Y., Wu, L., and Deng, HW. (2021)
A gene-level methylome-wide association analysis identifies novel Alzheimer’s disease genes. Bioinformatics.Wu, C.*, Xu, G., Shen, X., and Pan, W.* (2020)
A regularization-based adaptive test for high-dimensional generalized linear models. Journal of Machine Learning Research, 21(128), 1-67.Wu, C. (2020)
Multi-trait genome-wide analyses of the brain imaging phenotypes in UK Biobank. Genetics, 215(4), 947-958.
(Highlight in Genetics August issue; presented as a platform presentation at ASHG 2019 Annual Meeting)Wu, C.* and Pan, W.* (2019)
Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes. Bioinformatics, 35(19), 3576-3583.Wu, C., Chen, J., Kim, J., and Pan, W. (2016) An adaptive association test for microbiome data. Genome Medicine, 8(1), 1-12.
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(1), 6479-6503. #, co-first author
Selected Software
We put all recent developed software into a lab github page.
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.
Grants
R03 AG070669, NIA
Contact PI, (Wu and Bradley), 01-01-21 – 12-31-22
Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease
The Committee on Faculty Research Support, FSU
PI, 05-07-20 – 06-30-20
Novel Machine Learning Methods for Alzheimer’s Disease
First Year Assistant Professor Grant, FSU
PI, 05-08-19 - 08-06-19
Novel Statistical Methods for Transcriptome-wide Association Studies
Teaching
The opportunity for teaching is one of the key reasons I love academia. For me, teaching can be described as a rewarding and fulfilling experience. I am the instructor for the following courses.
2020 Fall: STA5934 Statistical Genetics. https://www.stat.fsu.edu/sites/g/files/upcbnu1811/files/STA5934-02-Fall20.pdfSyllabus]
2018 Fall to 2020 Spring, 2021 Spring: STAT 4321/4323 Introduction of Math Stat
Selected Presentations
I enjoy sharing ideas and presenting my works. I attend JSM, ENAR, and ASHG regularly.
Multi-trait genome-wide analyses of the brain imaging phenotypes in UK Biobank
Platform presentation at ASHG 2019
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Oral presentation at IGES 2018
An adaptive association test for microbiome data
Presented at 2016 JSM, ENAR
An adaptive test on high dimensional parameters in GLMs
Presented at 2017 JSM, ENAR
Awards
Dean's Faculty Travel Award, Florida State University, 2020
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
Contact
Chong Wu
314 OSB, 117 N. Woodward Ave.
P.O. Box 3064330, Tallahassee, FL, 32306-4330
E-mail: cwu3@fsu.edu