A statistical simulator scDesign for rational scRNA-seq experimental design
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 ]
EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences
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 ]
Matched bipartite block model with covariates
32. Razaee, Z.S., Amini, A.A., and Li, J.J. (2019). Matched bipartite block model with covariates. Journal of Machine Learning Research 20(34):1-44.
Review of “Statistical modeling and machine learning for molecular biology” by Moses, A.M.
31. Li, J.J. (2019). Review of “Statistical modeling and machine learning for molecular biology” by Moses, A.M. The American Statistician 73(1):103-104.
Word and sentence embedding tools to measure semantic similarity of Gene Ontology terms by their definitions
30. Duong, D., Ahmad, W.U., Eskin, E., Chang, K.-W., and Li, J.J. (2019). Word and sentence embedding tools to measure semantic similarity of Gene Ontology terms by their definitions. Journal of Computational Biology 26(1):38-52. [ SOFTWARE ]
Modeling and analysis of RNA-seq data: a review from a statistical perspective
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.
Spliceosome profiling visualizes operations of a dynamic RNP at nucleotide resolution
28. Burke, J.E., Longhurst, A.D., Merkurjev, D., Sales-Lee, J., Rao, B., Moresco, J.J., Yates III, J.R., Li, J.J., and Madhani, H.D. (2018). Spliceosome profiling visualizes operations of a dynamic RNP at nucleotide resolution. Cell 173(4):1014-1030.e17.
MSIQ: Joint Modeling of Multiple RNA-seq Samples for Accurate Isoform Quantification
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 ]
An accurate and robust imputation for single cell RNA-seq data
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 ]
Neyman-Pearson (NP) classification algorithms and NP receiver operating characteristics (NP-ROC)
25. Tong, X.*, Feng, Y.*, and Li, J.J. (2018). Neyman-Pearson classification algorithms and NP receiver operating characteristics. Science Advances 4(2):eaao1659. [ SOFTWARE ] [ VIDEO ] [ Francis X. Diebold’s Blog on NP Classification ]