Single-cell biological network inference using a heterogeneous graph transformer

Anjun Ma, Xiaoying Wang, Jingxian Li, Cankun Wang, Tong Xiao, Yuntao Liu, Hao Cheng, Juexin Wang, Yang Li, Yuzhou Chang, Jinpu Li, Duolin Wang, Yuexu Jiang, Li Su, Gang Xin, Shaopeng Gu, Zihai Li, Bingqiang Liu (), Dong Xu () and Qin Ma ()
Additional contact information
Anjun Ma: The Ohio State University
Xiaoying Wang: Shandong University
Jingxian Li: Shandong University
Cankun Wang: The Ohio State University
Tong Xiao: The Ohio State University
Yuntao Liu: Shandong University
Hao Cheng: The Ohio State University
Juexin Wang: University of Missouri
Yang Li: The Ohio State University
Yuzhou Chang: The Ohio State University
Jinpu Li: University of Missouri
Duolin Wang: University of Missouri
Yuexu Jiang: University of Missouri
Li Su: University of Missouri
Gang Xin: The Ohio State University
Shaopeng Gu: The Ohio State University
Zihai Li: The Ohio State University
Bingqiang Liu: Shandong University
Dong Xu: University of Missouri
Qin Ma: The Ohio State University

Nature Communications, 2023, vol. 14, issue 1, 1-18

Abstract: Abstract Single-cell multi-omics (scMulti-omics) allows the quantification of multiple modalities simultaneously to capture the intricacy of complex molecular mechanisms and cellular heterogeneity. Existing tools cannot effectively infer the active biological networks in diverse cell types and the response of these networks to external stimuli. Here we present DeepMAPS for biological network inference from scMulti-omics. It models scMulti-omics in a heterogeneous graph and learns relations among cells and genes within both local and global contexts in a robust manner using a multi-head graph transformer. Benchmarking results indicate DeepMAPS performs better than existing tools in cell clustering and biological network construction. It also showcases competitive capability in deriving cell-type-specific biological networks in lung tumor leukocyte CITE-seq data and matched diffuse small lymphocytic lymphoma scRNA-seq and scATAC-seq data. In addition, we deploy a DeepMAPS webserver equipped with multiple functionalities and visualizations to improve the usability and reproducibility of scMulti-omics data analysis.

Date: 2023
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DOI: 10.1038/s41467-023-36559-0

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