MultiGATE: Integrative Analysis and Regulatory Inference in Spatial Multi-Omics Data
Can Yang
Co-Author
The Hong Kong University of Science and Technology
Jinzhao Li
First Author
The Chinese University of Hong Kong
Jishuai MIAO
Presenting Author
The Chinese University of Hong Kong
Wednesday, Aug 6: 2:20 PM - 2:35 PM
1853
Contributed Papers
Music City Center
New spatial multi-omics technologies, which jointly profiles transcriptome and epigenome/protein markers for the same tissue section, have expanded the frontiers of spatial techniques. Here we introduce MultiGATE, which utilizes a two-level graph attention auto-encoder to integrate the multi-modality and spatial information in spatial multi-omics data. The key feature of MultiGATE is that it simultaneously performs embedding of the spatial pixels and infers the cross-modality regulatory relationship, which allows deeper data integration and provides insights on transcriptional regulation. We evaluated the performance of MultiGATE on spatial multi-omics datasets obtained from different tissues and platforms. Through effectively integrating spatial multi-omics data, MultiGATE both enhances the extraction of latent embeddings of the pixels and boosts the inference of transcriptional regulation for cross-modality genomic features.
Data Integration
Spatial multi-omics data
Main Sponsor
Section on Statistics in Genomics and Genetics
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