Wei Vivian Li

PhD Student in Statistics at UCLA (2014-2019)
Research interest: 

Wei (Vivian) is an Assistant Professor in the Department of Biostatistics and Epidemiology at the Rutgers University. She obtained her Ph.D. degree in Statistics from UCLA. Prior to that, she had a B.S. in Statistics from Huazhong University of Science and Technology. During her PhD, she has developed and improved statistical methods to uncover the hidden information in large-scale genomic data. Her research focused on statistical modeling of both tissue-level and single-cell RNA sequencing data, and various applications in practical biological and biomedical questions. She was also interested in the comparative analysis based on transcriptomic or epigenomic profiles from multiple tissues or cell types. She enjoys both the development of statistical methods and the application of these methods to real-world problems.

Homepage ] [ Github ]

Research interests:


  1. Cost-sensitive classification methods
  2. Statistical modeling of bulk RNA-seq data
    • Transcript assembly and quantification
    • Statistical inference
    • Biomedical applications to cancer samples
  3. Statistical modeling of single-cell RNA-seq data
    • Imputation of gene expression
    • Experimental design
  4. Comparative transcriptomics and epigenomics

Currently Tenure-track Assistant Professor in the Department of Biostatistics and Epidemiology at Rutgers University.


52. Jiang, R., Li, W.V., and Li, J.J. (2021). mbImpute: an accurate and robust imputation method for microbiome data. Genome Biology 22:192. [ UCLA NEWS ] [ SOFTWARE ] | [ PDF ]

36. Li, W.V.*, Li, S.*, Tong, X., Deng, L., Shi, H., and Li, J.J. (2019). AIDE: annotation-assisted isoform discovery with high precision. Genome Research 29:2056–2072. [ UCLA NEWS ] [ SOFTWARE ] [ DATA ] [ COVER ART ]

34. Li, W.V. and Li, J.J. (2019). A statistical simulator scDesign for rational scRNA-seq experimental design. Bioinformatics 35(14):i41–i50. [ ISMB/ECCB 2019 ] [ SOFTWARE ]

33. Ge, X.*, Zhang, H.*, Xie, L., Li, W.V., Kwon, S.B., and Li, J.J. (2019). EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences. Nucleic Acids Research 47(13):e77. [ SOFTWARE ] [ WEBSITE ]

29. Li, W.V. and Li, J.J. (2018). Modeling and analysis of RNA-seq data: a review from a statistical perspective. Quantitative Biology 6(3):195–209.

27. Li, W.V.*, Zhao, A., Zhang, S., and Li, J.J.* (2018). MSIQ: joint modeling of multiple RNA-seq samples for accurate isoform quantification. Annals of Applied Statistics 12(1):510–539. [ SOFTWARE ] [ COLOR PDF ]

26. Li, W.V. and Li, J.J. (2018). An accurate and robust imputation method scImpute for single-cell RNA-seq data. Nature Communications 9:997. [ UCLA NEWS ] [ SOFTWARE ]

19. Li, W.V.Chen, Y., and Li, J.J. (2017). TROM: a testing-based method for finding transcriptomic similarity of biological samples. Statistics in Biosciences 9(1):105–136. [ SOFTWARE ]

14. Li, W.V.Razaee, Z.S., and Li, J.J. (2016). Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states. BMC Genomics 17(Supp 1):10. [ SOFTWARE ]