Wenpin Hou, PhD
Dr. Hou's research focuses on developing novel statistical machine learning methods to tackle the challenges in the intersection of statistics and data science (data in single-cell genomics, epigenomics, and spatial transcriptomics), mathematical modeling of gene regulatory networks, and ultimately understanding gene regulatory mechanisms. Dr. Hou is particularly interested in developing methods for modeling the spatio-temporal patterns in single-cell and spatial genomics and epigenomics data using Bayesian framework with functional data analysis. Dr. Hou actively collaborates in various aspects of cancer, immunology, infectious disease, developmental processes, obesity, maternal and child health, and health disparity. The outcomes are expected to lead to a deeper understanding of regulatory mechanisms and new targeted therapy for various diseases that help the broad community.
- Assistant Professor of Biostatistics
Credentials & Experience
Education & Training
- BS, 2013 Sun Yat-sen University
- PhD, 2017 The University of Hong Kong
- Fellowship: 2022 Johns Hopkins University
- Biostatistical Methods
- Chronic disease
Hou, W. and Ji, Z. 2022. Decomposing spatial heterogeneity of cell trajectories with Paella. Preprint in bioRxiv. PMID/PMCID to be announced. Software: Paella. (In Journal Review)
Hou, W., Ji, Z., Chen, Z., Wherry, E.J., Hicks, S.C. and Ji, H., 2021. A statistical framework for differential pseudotime analysis with multiple single-cell RNA-seq samples. Preprint in bioRxiv. PMID: 34282418. PMCID: PMC8288148. Software: Lamian. (In Journal Revision)
Hou, W. and Ji, Z., 2022. Single-cell unbiased visualization with SCUBI. Cell Reports Methods, 100135, 2022. Software: SCUBI. PMID: 35224531. PMCID: PMC8871596
Hou, W., Ji, Z., Ji, H. and Hicks, S.C., 2020. A systematic evaluation of single-cell RNA-sequencing imputation methods. ‚Ä®Genome Biology 21, 218. PMID: 32854757. PMCID: PMC7450705.
Ji, Z., Zhou, W., Hou, W. and Ji, H., 2020. SCATE: single-cell ATAC-seq signal extraction and enhancement. Genome ‚Ä®Biology, 21,161. PMID: 32620137. PMCID: PMC7333383. Software: SCATE. SCATEData.