Yiwen Liu

Interests

Research

Big data analytics, statistical learning for high-dimensional data, multiple sources data fusion, and bioinformatics.

Courses

Scholarly Contributions

Journals/Publications

• Zhang, M., Parker, J., An, L., Liu, Y., & Sun, X. (2025). Flexible analysis of spatial transcriptomics data (FAST): a deconvolution approach. BMC Bioinformatics, 26(1), 35.
• Valenti, M. A., Farland, L. V., Huang, K., Liu, Y., Beitel, S. C., Jahnke, S. A., Hollerbach, B., St., C., Gulotta, J. J., Kolar, J. J., & others, . (2024). Evaluating the Effect of Depression, Anxiety, and Post-Traumatic Stress Disorder on Anti-M"ullerian Hormone Levels Among Women Firefighters. Journal of Women's Health.
• Sun, X., Liu, Y., Zhong, W., & Li, B. (2022). B-scaling: A novel nonparametric data fusion method. The Annals of Applied Statistics, 16(3). doi:10.1214/21-aoas1537
• Liu, Y., Zhong, W., & Zeng, P. (2021). A Model-free Variable Screening Method Based on Leverage Score. Journal of the American Statistical Association, 1-12. doi:10.1080/01621459.2021.1918554
• Zhang, M., Liu, Y., Zhou, H., Watkins, J., & Zhou, J. (2021). A novel nonlinear dimension reduction approach to infer population structure for low-coverage sequencing data. BMC bioinformatics, 22(1). doi:10.1186/s12859-021-04265-7
  More info

  BACKGROUND: Low-depth sequencing allows researchers to increase sample size at the expense of lower accuracy. To incorporate uncertainties while maintaining statistical power, we introduce MCPCA_PopGen to analyze population structure of low-depth sequencing data. RESULTS: The method optimizes the choice of nonlinear transformations of dosages to maximize the Ky Fan norm of the covariance matrix. The transformation incorporates the uncertainty in calling between heterozygotes and the common homozygotes for loci having a rare allele and is more linear when both variants are common. CONCLUSIONS: We apply MCPCA_PopGen to samples from two indigenous Siberian populations and reveal hidden population structure accurately using only a single chromosome. The MCPCA_PopGen package is available on https://github.com/yiwenstat/MCPCA_PopGen .
• Sun, X., Liu, Y., & An, L. (2020). EDGE: Ensemble Dimensionality Reduction and Feature Gene Extraction for Single-cell RNA-seq Data. Nature Communications.

Presentations

• Liu, Y. (2019, May). B-scaling: a novel nonparametric data fusion method. New England Statistics Symposium.
• Liu, Y. (2019, October). Trajectory inference using single-cell transcriptomics data. TRIPODS RWG 6.
• Liu, Y. (2018, Dec). B-scaling: a novel nonparametric data fusion method. International Conference on Big Data and Information Analytics. Houston, TX.
• Liu, Y. (2018, Sep). Statistical leverage and its usage in variable screening. Department seminar, Department of Epidemiology and Biostatistics. Tucson, AZ.
• Liu, Y., Watkins, J., & Encinas, A. (2018, Sep). Sodium Channels Pathologies and Statistical Issues in Pathogenicity Prediction. Quantitative Biology Colloquium. Tucson, AZ: Department of Mathematics.

Others

• Liu, Y. (2018, Jun). Statistical learning for high-dimensional and complex data session chair. ICSA Applied Statistics Symposium.