BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

• Published in: Genome Biology Vol. 23; no. 1; p. 168
• Main Authors: Li, Zheng, Zhou, Xiang
• Format: Journal Article
• Language: English
• Published: England BioMed Central 04.08.2022; BMC
• Subjects: Bayes Theorem; Bayesian analysis; Bayesian theory; Cell type; Cluster Analysis; Clustering analysis; Computer applications; cortex; data collection; Datasets; domain; Gene expression; genome; Hypothalamus; landscapes; Localization; Method; Multi-sample analysis; Multi-scale analysis; Performance evaluation; Simulation; Spatial discrimination; Spatial domain; Spatial transcriptomics; Transcriptome; Transcriptomics; BASS; Bayesian hierarchical model; Multi-scale analysis; Spatial domain; Spatial transcriptomics; Clustering analysis; Tissue section; Cell type; Multi-sample analysis

Spatial transcriptomic studies are reaching single-cell spatial resolution, with data often collected from multiple tissue sections. Here, we present a computational method, BASS, that enables multi-scale and multi-sample analysis for single-cell resolution spatial transcriptomics. BASS performs cel...