For a list of publications, see also ResearchGate or Google schoolar.

Preprint

• Wei Liu, Xiao Zhang^c, Xiaoran Chai, Zhenqian Fan, Huazhen Lin, Jinmiao Chen, Lei Sun, Tianwei Yu, Joe Yeong, and Jin Liu*. Fast: a fast and scalable factor analysis for spatially aware dimension reduction of multi-section spatial transcriptomics data. PDF in biorxiv . CRAN R package, Github R package, and FAST’s usage and applications.

Publication

1. Statistical Method and Thoery

• [8] Wei Liu, Guizhen Li, Ling Zhou*, Lan Luo (2025). High-dimensional large-scale mixed-type data imputation under missing at random. SCIENCE CHINA Mathematics. 46, 969–1000, PDF, Github Matlab tool

• [7] Wei Liu, Qingzhi Zhong* (2024). High-dimensional covariate-augmented Overdispersed Poisson factor models. Biometrics, 80(2), ujae031, PDF in Biometrics, PDF in arxiV. CRAN R package, Github R package, and COAP’s usage and applications.

• [6] Jinyu Nie, Zhilong Qin, Wei Liu*, (2024). High-dimensional overdispersed generalized factor model with application to single-cell sequencing data analysis, Statistics in Medicine. CRAN R package, Github R package, and OverGFM’s usage and applications.

• [5] Wei Liu, Lan Luo*, Ling Zhou* (2023). Online missing value imputation for high-dimensional mixed data via generalized factor models. Computational Statistics & Data Analysis, 187, 107822 PDF, Github R package

• [4] Wei Liu, Huazhen Lin*, Jin Liu & Shurong Zheng (2023) Two-directional simultaneous inference for high-dimensional models, Journal of Business & Economic Statistics, 42:1, 298-309. PDF, CRAN R package, Github R package

• [3] Wei Liu, Huazhen Lin*, Li Liu, Yanyuan Ma, Ying Wei, Yi Li (2023). Supervised structural learning of semiparametric regression on high-dimensional correlated covariates with applications to eQTL studies. Statistics in Medicine, 42(18), 3145-3163

• [2] Wei Liu, Huazhen Lin*, Shurong Zheng & Jin Liu (2023). Generalized factor model for ultra-high dimensional correlated variables with mixed types. Journal of the American Statistics Association, 118(542), 1385-1401. PDF, Matlab tool, CRAN R package, Github R package, and GFM’s usage and applications.

• [1] Huazhen Lin*, Wei Liu, & Wei Lan (2021). Regression Analysis with individual-specific patterns of missing covariates. Journal of Business & Economic Statistics, 39(1), 179-188. PDF, CRAN R package, Github R package, and ILSE’s usage and applications.

2. Statistical Genomics (Single-Cell RNA-seq/Spatial transcriptomics)

• [3] Peng Xie^c, Juan Shen^c, Yi Yang^c, Xinrui Wang^c, Wei Liu^c, Hailong Cao^c, Yanying Zheng, Chen Wu, Guangyao Mao, Linjin Chen, Jingjing He, Weiheng Zheng, Zepu Yang, Xiao Zhang, Xu Jiang, Xianfa Yang, Ke Fang, Zhao Zhang, Xin Xue, Xueting Chen, Chaoyi Wang, Xing Liu, Lin Liu, Xuebiao Yao, Naihe Jing, Wei Xie, Jin Liu*, Hua Cao*, Zhuojuan Luo*, Xiaodong Fang*, Chengqi Lin* (2025), Digital reconstruction of full embryos during early mouse organogenesis. Cell, Online, PDF, Github R package

• [2] Wei Liu, Xu Liao ^c, Ziye Luo, Yi Yang, Mai Chan Lau, Yuling Jiao, Xingjie Shi, Weiwei Zhai, Hongkai Ji, Joe Yeong, Jin Liu* (2023). Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST. Nature Communications, 14, 296. PDF, CRAN R package, Github R package and PRECAST’s usage and applications.

• [1] Wei Liu, Xu Liao, Yi Yang, Huazhen Lin, Joe Yeong, Xiang Zhou*, Xingjie Shi* & Jin Liu* (2022). Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data, Nucleic Acids Research, gkac219. PDF, CRAN R package, Github R package and DR.SC’s usage and applications.

Posters

• A covariate-augmented overdispersed Poisson factor model is proposed to jointly perform a high-dimensional Poisson factor analysis and estimate a large coefficient matrix for overdispersed count data, callded COAP published on Biometrics. Date: 2024-06-25.

• Our PRECAST method is recognized as the representative method for spatial domain identification in a Science paper. Date: 2024-05-24.

• A computational framework for integrating and analyzing multiple spatially resolved transcriptomics (SRT) datasets, callded PRECAST published on Nature Communications. Date: 2023-01-20.

• A computational framework for joint dimension reduction and spatial clustering, callded DR-SC published on Nucleic Acids Research. Date: 2022-05-29.

* Corresponding author, ^c co-first author.