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(selected)

1. Statistical Method and Thoery

• [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] Wei Liu, Guizhen Li, Lan Luo, Ling Zhou* (2024). High-dimensional large-scale mixed-type data imputation under missing at random. SCIENCE CHINA Mathematics. Accepted, Github Matlab tool

• [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)

• [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

• 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.