Deciphering spatial domains from spatial multi-omics with SpatialGlue
Agency for Science, Technology and Research · Institute of Molecular and Cell Biology · +9 more institutions
Abstract
Advances in spatial omics technologies now allow multiple types of data to be acquired from the same tissue slice. To realize the full potential of such data, we need spatially informed methods for data integration. Here, we introduce SpatialGlue, a graph neural network model with a dual-attention mechanism that deciphers spatial domains by intra-omics integration of spatial location and omics measurement followed by cross-omics integration. We demonstrated SpatialGlue on data acquired from different tissue types using different technologies, including spatial epigenome-transcriptome and transcriptome-proteome modalities. Compared to other methods, SpatialGlue captured more anatomical details and more…
Citation impact
- FWCI
- 28.04
- Percentile
- 100%
- References
- 27
Authors
20- YLYahui LongCorresponding
Agency for Science, Technology and Research, Institute of Molecular and Cell Biology
- KSKok Siong Ang
Agency for Science, Technology and Research, Institute of Molecular and Cell Biology
- RSRaman Sethi
Agency for Science, Technology and Research
- SLSha Liao
BGI Group (China), BGI Research
- YHYang Heng
BGI Group (China), BGI Research
Topics & keywords
- Epigenome
- Omics
- Computer science
- Spatial analysis
- Data integration
- Computational biology
- Transcriptome
- Biology