Metadata-Version: 2.1
Name: SpatialGlue
Version: 1.0.0
Summary: Integrated analysis of spatial multi-omics with SpatialGlue
Home-page: https://github.com/JinmiaoChenLab/SpatialGlue
Author: Yahui Long
Author-email: longyh@immunol.a-star.edu.sg
License: MIT
Description-Content-Type: text/markdown
License-File: LICENSE.md

SpatialGlue is a novel deep learning method for integrating spatial multi-omics data in a spatially informed manner. It utilizes a cycle graph neural network with a dual-attention mechanism to learn the significance of each modality at cross-omics and intra-omics integration. The method can accurately aggregate cell types or cell states at a higher resolution on different tissue types and technology platforms. Besides, it can provide interpretable insights into cross-modality spatial correlations. SpatialGlue is computationally efficient and it only requires about 5 mins for spatial multi-omics data at single-cell resolution (e.g., Spatial-ATAC-RNA-seq data, ~10,000 spots). 
