# transFusion: a novel comprehensive platform for integration analysis of single-cell and spatial transcriptomics

## TL;DR

transFusion is a web-based platform that integrates single-cell and spatial transcriptomics data to analyze tissue organization and interactions with minimal computational expertise.

## Contribution

transFusion introduces a comprehensive platform for multimodal integration of scRNA-seq and 10× Visium data with 12 key analytical functions.

## Key findings

- transFusion enables intercellular dependency analysis and ligand–receptor coexpression visualization.
- Case studies demonstrated its utility in exploring tissue architecture and spatial gradients with minimal expertise.
- The platform supports end-to-end workflows for spatial transcriptomics data integration.

## Abstract

Understanding spatial organization, intercellular interactions, and regulatory networks within the spatial context of tissues is crucial for uncovering complex biological processes and disease mechanisms. Spatial transcriptomics technologies have revolutionized this field by enabling the spatially resolved profiling of gene expression. 10× Visium has emerged as the predominant spatial technology, but its low resolution and the complexity of integrating multimodal datasets present significant analytical challenges, particularly for researchers with limited computational and statistical expertise. Current spatial transcriptomics analysis platforms generally fall short of effectively integrating multimodal data and maximizing the utility of spatial information—such as uncovering complex cellular spatial dependencies, multimodal gradient patterns, and spatial coexpression of ligand–receptor pairs and regulatory networks related to disease or biological states—thereby limiting their ability to provide comprehensive end-to-end analytical workflows when analyzing 10× Visium data.

To address these limitations, we developed transFusion, a novel, advanced web-based platform specializing in the most comprehensive and effective integration analysis of scRNA-seq and 10× Visium spatial transcriptomics data. transFusion offers 12 key functions, from basic visualization to advanced analyses, including intercellular dependency analysis, ligand–receptor coexpression identification and visualization, and spatial multimodal gradient variation patterns. Two case studies were used to demonstrate transFusion’s capabilities in exploring tissue architecture, intercellular communication, dependency networks, and multimodal gradient variation patterns with minimal computational skills and statistical expertise. transFusion provides a flexible and powerful framework for multimodal data integration analysis.

transFusion is freely available at https://github.com/WQLin8/transFusion.