Revealing spatial multimodal heterogeneity in tissues with SpaTrio.

ABSTRACT: Capturing and depicting the multimodal tissue information of tissues at the spatial scale remains a significant challenge owing to technical limitations in single-cell multi-omics and spatial transcriptomics sequencing. Here, we developed a computational method called SpaTrio that can build spatial multi-omics data by integrating these two datasets through probabilistic alignment and enabling further analysis of gene regulation and cellular interactions. We benchmarked SpaTrio using simulation datasets and demonstrated its accuracy and robustness. Next, we evaluated SpaTrio on biological datasets and showed that it could detect topological patterns of cells and modalities. SpaTrio has also been applied to multiple sets of actual data to uncover spatially multimodal heterogeneity, understan

SUBMITTER: Yang P 

PROVIDER: S-EPMC10726534 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature