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

Area of Science:

• Genomics and Bioinformatics
• Systems Biology
• Computational Biology

Background:

• Spatial transcriptomics, particularly 10X Genomics Visium, is vital for understanding tissue biology but faces challenges in data integration and analysis.
• Existing platforms struggle to fully leverage spatial information for complex analyses like intercellular dependencies and multimodal gradients.
• Researchers with limited computational expertise face significant hurdles in analyzing these datasets.

Purpose of the Study:

• To develop an advanced, web-based platform for integrated analysis of scRNA-seq and 10X Visium spatial transcriptomics data.
• To provide a user-friendly solution for researchers to explore tissue architecture, intercellular communication, and regulatory networks.
• To overcome the limitations of current platforms in handling multimodal spatial data.

Main Methods:

• Development of transFusion, a novel web-based platform with 12 key functions.
• Integration of scRNA-seq and 10X Visium spatial transcriptomics data.
• Implementation of advanced analyses including intercellular dependency, ligand-receptor co-expression, and spatial gradient pattern analysis.

Main Results:

• transFusion offers comprehensive integration and analysis of multimodal spatial transcriptomics data.
• The platform enables exploration of tissue architecture, intercellular communication, and multimodal gradient variations.
• Case studies demonstrate transFusion's effectiveness with minimal computational and statistical expertise.

Conclusions:

• transFusion provides a flexible and powerful framework for multi-modal spatial transcriptomics data integration and analysis.
• The platform democratizes advanced spatial data analysis for a wider research community.
• It facilitates deeper insights into biological processes and disease mechanisms through spatial context.