Representative Papers:

[1] Y. Cheng, B. Cai, H. Li, X. Zhang, G. D’Souza, S. Shrestha, A. Edmonds, J. Meyers, M. Fischl, S. Kassaye, K. Anastos, M. Cohen, B. E. Aouizerat, K. Xu, H. Zhao (2024) HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data

[2] B. Cai, J. Zhang, H. Li, C. Su, H. Zhao (2024) Statistical inference of cell-type proportions estimated from bulk expression data. Journal of American Statistical Association, in press.

[3] C. Su, J. Zhang, H. Zhao (2024) Estimating cell-type-specific gene co-expression networks from bulk gene expression data with an application to Alzheimer’s disease. Journal of American Statistical Association, 119: 811-824.

[4] Li H, Lin Y, He W, Han W, Xu X, Xu C, Gao E, Zhao H, Gao X. (2024) SANTO: a coarse-to-fine alignment and stitching method for spatial omics. Nature Communications, 15: 6048.

[5] S. Park, E. R. Lee, H. Zhao (2024) Low-rank regression models for multiple binary responses and their applications to cancer cell-line encyclopedia data. Journal of American Statistical Association, 119: 202-216.

[6] B. Zhu, Y. Wang, L-T Ku, D. van Dijk, L. Zhang, D. A. Halfer, H. Zhao (2023) scNAT: a deep learning method for integrating paired single cell RNA and T cell receptor sequencing profiles. Genome Biology, 24: 292.

[7] Su C, Xu Z, Shan X, Cai B, Zhao H, Zhang J (2023) Cell-type-specific co-expression inference from single cell RNA-sequencing data. Nature Communications, 14: 4846.

[8] B. Zhu, H. Li, L. Zhang, S. S. Chandra, H. Zhao (2022) A Markov random field model-based approach for differentially expressed gene detection from single-cell RNA-seq data. Briefings in Bioinformatics, 23: bbac166.

[9] Y. Wang, T. Liu, H. Zhao (2022) ResPAN: a powerful batch correction model for scRNA-seq data through residual adversarial networks. Bioinformatics, 30: 3942-3949.

[10] D. Tang, S. Park, H. Zhao (2022) SCADIE: simultaneous estimation of cell type proportions and cell type-specific gene expressions using SCAD-based iterative estimating procedure. Genome Biology, 23: 129.

[11] Y. Wang, H. Zhao (2022) Non-linear archetypal analysis of single-cell RNA-seq data by deep autoencoders. PLOS Computational Biology, 18: e1010025.

[12] H. Li, B. Zhu, Z. Xu, T. Adams, N. Kaminski, H. Zhao (2021) A Markov random field model for network-based differential expression analysis of single-cell RNA-seq data. BMC Bioinformatics, 22: 524.

[13] D. Tang, S. Park, H. Zhao (2020) NITUMID: Nonnegative Matrix Factorization-based Immune-TUmor MIcroenvironment Deconvolution. Bioinformatics, 36: 1344-1350.

[14] Y. Liu, J. Warren, H. Zhao (2019) A hierarchical Bayesian model for single-cell clustering using RNA-sequencing data. Annals of Applied Statistics, 13: 1733-1752.