Lei Cao, Chao Yang, Luni Hu, Wenjian Jiang, Yating Ren, Tianyi Xia, Mengyang Xu, Yishuai Ji, Mei Li, Xun Xu, Yuxiang Li, Yong Zhang, Shuangsang Fang
BACKGROUND: Cell clustering is a pivotal aspect of spatial transcriptomics (ST) data analysis as it forms the foundation for subsequent data mining. Recent advances in spatial domain identification have leveraged graph neural network (GNN) approaches in conjunction with spatial transcriptomics data. However, such GNN-based methods suffer from representation collapse, wherein all spatial spots are projected onto a singular representation. Consequently, the discriminative capability of individual representation feature is limited, leading to suboptimal clustering performance...
January 2, 2024: GigaScience