JinmiaoChenLab/SpatialGlue: SpatialGlue
Description
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).
Files
JinmiaoChenLab/SpatialGlue-v1.0.0.zip
Files
(236.7 MB)
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md5:01a7dc85ff940d80993ac7e1fda83515
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md5:dd2a6b2d2fedbea0c8ce1431f5155638
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Additional details
Related works
- Is supplement to
- https://github.com/JinmiaoChenLab/SpatialGlue/tree/v1.0.0 (URL)