FGOT - Multiomics Integration

FGOT: Feature-Guided Optimal Transport

This project focuses on Feature-Guided Optimal Transport (FGOT) for the integration and analysis of single-cell and spatial multi-omics data.

Overview

We use feature-guided optimal transport for the integration of cells across different modalities. My contributions encompass a portion of the coding, experiments, and the co-authorship of the manuscript.

Key Features

• Cross-modal integration: Seamlessly integrate data from different omics layers (scRNA-seq, spatial transcriptomics, etc.)
• Feature-guided: Leverage biological features to guide the optimal transport process
• Interpretable: The method provides interpretable mappings between cell states

Publication

This work has been published in Cell Systems:

Yang, Chenghui and He, Zhentao and Nie, Qing and Zhang, Lihua. “Interpretable Data Integration for Single Cell and Spatial Multi-Omics.” Cell Systems, 2026.

Read the paper

Links

• GitHub Repository

(Yang et al., 2026)