Biological network inference from single-cell multi-omics data using heterogeneous graph transformer

Ma, A.; Wang, X.; Wang, C.; Li, J.; Xiao, T.; Wang, J.; Chang, Y.; Li, Y.; Liu, Y.; Gu, S.; Wang, D.; Jiang, Y.; Su, L.; Li, Z.; Liu, B.; Xu, D.; Ma, Q.

doi:10.1101/2021.10.31.466658

bioRxiv · 10.1101/2021.10.31.466658

Biological network inference from single-cell multi-omics data using heterogeneous graph transformer

Ma, A.·Wang, X.·Wang, C.·Li, J.·Xiao, T.·Wang, J.·Chang, Y.·Li, Y.·Liu, Y.·Gu, S.·Wang, D.·Jiang, Y.·Su, L.·Li, Z.·Liu, B.·Xu, D.·Ma, Q.

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Abstract

We present DeepMAPS (Deep learning-based Multi-omics Analysis Platform for Single-cell data) for biological network inference from single-cell multi-omics (scMulti-omics). DeepMAPS includes both cells and genes in a heterogeneous graph to simultaneously infer cell-cell, cell-gene, and gene-gene relations. The multi-head attention mechanism in a graph transformer considers the heterogeneous relation among cells and genes within both local and global context, making DeepMAPS robust to data noise and scale. We benchmarked DeepMAPS on 18 scMulti-omics datasets for cell clustering and biological network inference, and the results showed that our method outperformed various existing tools. We further applied DeepMAPS on lung tumor leukocyte CITE-seq data and matched diffuse small lymphocytic lymphoma scRNA-seq and scATAC-seq data. In both cases, DeepMAPS showed competitive performance in cell clustering and predicted biologically meaningful cell-cell communication pathways based on the inferred gene networks. Note that we deployed a webserver using DeepMAPS implementation equipped with multiple functions and visualizations to improve the feasibility and reproducibility of scMulti-omics data analysis. Overall, DeepMAPS represents a heterogeneous graph transformer for single-cell study and may benefit the use of scMulti-omics data in various biological systems.

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Ma, A., Wang, X., Wang, C., Li, J., Xiao, T., Wang, J., Chang, Y., Li, Y., Liu, Y., Gu, S., Wang, D., Jiang, Y., Su, L., Li, Z., Liu, B., Xu, D., Ma, Q.. 2021-11-03. Biological network inference from single-cell multi-omics data using heterogeneous graph transformer. https://doi.org/10.1101/2021.10.31.466658

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