Wei Liu

FAST improves spatial dimension reduction for multi-section SRT data by modeling count data and spatial smoothness, showing better performance and speed on real datasets.

PRECAST integrates spatial transcriptomics data from multiple sources, improving cell and domain detection through probabilistic embedding, clustering, and alignment.

This paper introduces DR-SC, a method that jointly performs dimension reduction and spatial clustering for single-cell and spatial transcriptomics data, improving accuracy and biological relevance.

SC-MEB is a spatial clustering method for transcriptomics data that outperforms existing methods in clustering performance and scalability.