MultiGATE: Integrative Analysis and Regulatory Inference in Spatial Multi-Omics Data

Jishuai MIAO Co-Author
The Chinese University of Hong Kong
 
Ying Zhu Co-Author
Fudan University
 
Can Yang Co-Author
The Hong Kong University of Science and Technology
 
Zhixiang Lin Co-Author
The Chinese University of Hong Kong
 
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.

Keywords

Data Integration

Spatial multi-omics data 

Main Sponsor

Section on Statistics in Genomics and Genetics