SpaSEG: unsupervised deep learning for multi-task analysis of spatially resolved transcriptomics

Abstract Spatially resolved transcriptomics (SRT) for characterizing spatial cellular heterogeneities in tissue environments requires systematic analytical approaches to elucidate gene expression variations within their physiological context. Here, we introduce SpaSEG, an unsupervised deep learning...

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Bibliografiske detaljer

Principais autores:	Yong Bai, Xiangyu Guo, Keyin Liu, Bingjie Zheng, Yilin Wei, Yingyue Wang, Wenxi Zhang, Qiuhong Luo, Jianhua Yin, Liang Wu, Yuxiang Li, Yong Zhang, Ao Chen, Xiangdong Wang, Xun Xu, Chuanyu Liu, Xin Jin
Format:	Artigo
Sprog:	Inglês
Udgivet:	BMC 2025-07-01
Serier:	Genome Biology
Fag:	Spatially resolved transcriptomics Deep learning Spatial domain identification Multi-section integration Spatially variable gene Cell–cell interaction
Online adgang:	https://doi.org/10.1186/s13059-025-03697-1
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