About me

Hello, my name is Tianzhou (Charles) Ma, I am an Assistant Professor in Biostatistics at the Department of Epidemiology and Biostatistics of the School of Public Health at University of Maryland College Park. I received my PhD in Biostatistics from the University of Pittsburgh in 2018 and a MS in Biostatistics from Yale University in 2013. My research focuses on developing useful and timely statistical methods and softwares in genomics and bioinformatics, meta-analysis and data integration, statistical machine learning, Bayesian analysis, high-dimensional variable selection, as well as their application in cancer, neuroscience and epidemiology fields. I am actively seeking for collaborations with researchers in both methodology and application (not restricted to my current fields of research). Please also visit our research group at: www.umdbright.com

Link to my [CV]

Research interest

  • Meta-analysis and big data integration (e.g. multi-omics data (genotype, gene expression, epigenetic and proteomics data, etc.) integration, integration of neuroimaging and genetic data, etc.)
  • Statistical learning, clustering and high-dimensional variable selection
  • Bayesian analysis and hierarchical modeling
  • Application to neuroscience (e.g. severe mental illness and aging), cancer (e.g. Pan-cancer study) and epidemiology fields
  • And other new fields to be explored …

Recently, we have special interest in developing novel methods for imaging-genetic data integration, statistical genetic methods for post-GWAS analysis (e.g. fine mapping, Polygenic risk score (PRS), Mendelian randomization based causal inference, etc.) and in the fields of comparative genomics and functional genomics.

Recent highlighted publications

Notes: ^: co-first author; *: corresponding author; students underlined; [My Google Scholar Page]

[1] Ye Z^ , Mo C^, Liu S^, Hatch K, Gao S, Hong E, ..., Kochunov P*, Chen S* and Ma T*. (2021). White matter integrity and nicotine dependence: evaluating vertical and horizontal pleiotropy. Frontiers in Neuroscience, Accepted. [bioRxiv version]

[2] Ye Z^ , Ke H^ , Chen S, Cruz-Cano R, He X, Zhang J, Dorgan J, Milton D and Ma T*. (2021). Biomarker categorization in transcriptomic meta-analysis by concordant patterns with application to Pan-cancer studies. Frontiers in Genetics, Accepted. [Link] [software]

[3] Saegusa T, Zhao Z , Ke H , Ye Z , Xu Z, Chen S and Ma T*. (2021). Detecting survival-associated biomarkers from heterogeneous populations. Scientific Reports , Accepted. [pdf] [software]

[4] Ma T, Ren Z and Tseng GC. (2020). Variable screening with multiple studies. Statistica Sinica , 30(2): 925–953.[pdf]

[5] Mo C^, Ye Z^ , Hatch K, Zhang Y, Wu Q, Liu S and Kochunov P, Ma T* and Chen S*. (2021). Genetic Fine-mapping with Dense Linkage Disequilibrium Blocks: genetics of nicotine dependence. bioRxiv. [Link].

[6] Ma T^, Huo Z^, Kuo A^, Zhu L, ..., Song C and Tseng GC. (2019). MetaOmics - Comprehensive Analysis Pipeline and Web-based Software Suite for Transcriptomic Meta-Analysis. Bioinformatics . PMID: 30304367. [pdf] [software]

Collaboration

Methodology

Application

Research Support