Wenan Chen, PhD

Wenan Chen, PhD

  • Bioinformatics Research Scientist, R & D


Postdoctoral Fellowship, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
Postdoctoral Fellowship, 
Department of Biostatistics, Virginia  Commonwealth University, Richmond, VA
PhD, Computer Science, Virginia Commonwealth University, Richmond, VA
MS, Computer Science, Beijing University of Technology, Beijing, China
BS, Information Management and Information System, Beijing Information Technology Institute, Beijing, China


Dr. Wenan Chen got his training in computer science and later in statistical genetics as a postdoc before joining St Jude. His research interests mainly focus on statistical genetics, genomics, and bioinformatics.  By using proper and well-designed methods on big data arising from biomedical areas such as DNA & RNA sequencing data, and close collaborations with domain experts, he aims to stimulate more state-of-the-art methods development and more scientific discoveries about biology, diseases, and in the end better treatments of diseases.  

Research Interests

  • Identifying disease predisposition genes and variants using sequencing data
  • Fine mapping causal variants in genetic association studies
  • Single cell RNASeq data analysis, such as differential expression analysis, clustering

Selected Publications

Emilia M. Pinto, Bonald C. Figueiredo, Wenan Chen, Henrique C.R. Galvao, …, Gang Wu and Gerard P. Zambetti, XAF1 as a modifier of p53 function and cancer susceptibility, Science Advances, 2020, 6(26), eaba3231.

Wenan Chen, Silu Zhang, Justin Williams, Bensheng Ju, Bridget, Shaner, John Easton, Gang Wu, and Xiang Chen, A comparison of methods accounting for batch effects in differential expression analysis of UMI count based single cell RNA sequencing, Computational and Structural Biotechnology Journal, 2020, 18, pp. 861-873.

Daniel J. Schaid, Wenan Chen & Nicholas B. Larson, From genome-wide associations to candidate causal variants by statistical fine-mapping, Nature Reviews Genetics, 2018, 19, pp. 491-504. 

Wenan Chen, Yan Li, John Easton, David Finkelstein, Gang Wu, and Xiang Chen, UMI-count modeling and differential expression analysis for single-cell RNA sequencing, Genome Biology, 2018, 19. 

Wenan Chen, Shannon K. McDonnell, Stephen N. Thibodeau, Lori S. Tillmans, and Daniel J. Schaid, Incorporating Functional Annotations for Fine-Mapping Causal Variants in a Bayesian Framework Using Summary Statistics, Genetics, 2016, 204(3), pp. 933-958.

Jun Chen*, Wenan Chen*, Ni Zhao, Michael C. Wu, Daniel J. Schaid. Small-Sample Kernel Association Tests for Human Genetic and Microbiome Association Studies, Genetic Epidemiology, 2016, 40, pp.5-19. (*Co-first author)

Wenan Chen, Beth R. Larrabee, Inna G. Ovsyannikova, Richard B. Kennedy, Iana H. Haralambieva, Gregory A. Poland, Daniel J. Schaid. Fine Mapping Causal Variants with an Approximate Bayesian Method using Marginal Test Statistics, Genetics, (chosen by editors as the highlighted article), 2015, 200(3) pp. 719-736.

Wenan Chen and Daniel J. Schaid. PedBLIMP: extending linear predictors to impute genotypes in pedigrees, Genetic Epidemiology, 2014, 38, pp. 531-541.

Wenan Chen, Chunfeng Ren, Huaizhen Qin, Kellie J. Archer, Weiwei Ouyang, Nianjun Liu, Xingguang Luo, Xiaofeng Zhu, Shumei Sun, Guimin Gao. Smooth sequential Bonferroni procedures for GWAS in admixed populations incorporating admixture mapping information into association tests. Human Heredity, 2015, 79(2) pp. 80-92.

Wenan Chen, Xiangning Chen, Kellie J. Archer, Nianjun Liu, Zhongming Zhao, Shumei Sun, Guimin Gao. A Rapid Association Test Procedure Robust under Different Genetic Models Accounting for Population Stratification, Human Heredity, 2013, 75(1), pp. 13-33.

Wenan Chen, Guimin Gao, Srilaxmi Nerella, Christina M Hultman, Patrik KE Magnusson, Patrick F Sullivan, Karolina A Aberg and Edwin JCG van den Oord. MethylPCA: A toolkit to control for confounders in methylome-wide association studies, BMC Bioinformatics, 2013, 14:74

Shudong Wang*, Wenan Chen*, Xiangning Chen, Fengjiao Hu, Kellie J. Archer, Nianjun Liu, Shumei Sun and Guimin Gao. Double genomic control is not effective to correct for population stratification in Meta-analysis for genome-wide association studies. Frontiers in Genetics, 2012, 3:300. (*Co-first author).

Guimin Gao, Guolian Kang, Jiexun Wang, Wenan Chen, Huaizen Qin, Bo Jiang, Qizhai Li, Chuanyu Sun, Nianjun Liu, Kellie J Archer, David B Allison. A Generalized Sequential Bonferroni Procedure Using Smoothed Weights for Genome-Wide Association Studies Incorporating Information on Hardy-Weinberg Disequilibrium among Cases. Human Heredity. 2011, 73(1), pp. 1-13.

Wenan Chen, Xi Gao, Jiexun Wang, Chuanyu Sun, Wen Wan, Degui Zhi, Nianjun Liu, Xiangning Chen, Guimin Gao. Evaluation of association tests for rare variants using simulated data sets in the Genetic Analysis Workshop 17 data. BMC Proceedings. 2011, 5 Suppl 9: S86.

Wenan Chen, Charles Cockrell, Kevin Ward, Kayvan Najarian. Predictability of Intracranial Pressure Level in Traumatic Brain Injury: Features Extraction, Statistical Analysis and Machine Learning based Evaluation. International Journal of Data Mining and Bioinformatics, 2013, 8(4).

Wenan Chen, Kevin Ward, Qi Li, Vojislav Kecman, Kayvan Najarian, Nathan Menke. Agent based modeling of blood coagulation system: implementation using a GPU based high speed framework. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE Engineering in Medicine and Biology Society. 2011, pp: 145-148.

Wenan Chen, Rebecca Smith, Soo-Yeon Ji, and Kayvan Najarian. Automated Segmentation of Lateral Ventricles in Brain CT images. IEEE International Conference on Bioinformatics and Biomeidcine Workshops, (BIBMW 2008), 2008, pp. 48-55.

Last update: June 2020

For updates on COVID-19, please read.