MMSpa is a deep learning-based tool that enhances the identification of spatial domains in spatial transcriptomics studies.

ABSTRACT: Spatial transcriptome (ST) technologies have transformed the study of tissue structure by retaining the spatial distribution of gene expression. One major challenge in accurately identifying spatial domains is to extract domain-related information from spatial locations and gene expression. Here, we propose MMSpa, a masked graph attention autoencoder framework specifically designed to improve spatial domain identification. MMSpa incorporates an edge-removal strategy to construct an enhanced spatial graph to fundamentally address cross-domain interference and characterize clearer domain boundaries. By focusing on masked gene expression reconstruction, MMSpa learns stable latent representations that capture core biological features, facilitating the identification of similar spatial subdomai

SUBMITTER: Liu Y 

PROVIDER: S-EPMC12768284 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature