CellSP: Module discovery and visualization for subcellular spatial transcriptomics data

Area of Science:

• Molecular Biology
• Computational Biology
• Genomics

Background:

• Spatial transcriptomics allows studying mRNA distribution within cells, crucial for cellular function.
• Existing tools lack the capability to identify and interpret functionally relevant spatial patterns of subcellular transcript distribution.

Purpose of the Study:

• To present CellSP, a computational framework for identifying, visualizing, and characterizing consistent subcellular spatial patterns of mRNA.
• To introduce the concept of "gene-cell modules" with coordinated subcellular transcript distributions.

Main Methods:

• Development of the CellSP computational framework.
• Utilizing gene-cell modules to represent coordinated transcript distributions.
• Visualization and functional interpretation of spatial patterns.

Main Results:

• CellSP reliably identifies functionally significant modules across diverse tissues and technologies.
• Discovery of subcellular spatial phenomena related to myelination, axonogenesis, and synapse formation in the mouse brain.
• Identification of immune response modules in kidney cancer and myelination modules in Alzheimer's disease models.

Conclusions:

• CellSP provides a robust method for analyzing subcellular transcript spatial patterns.
• The framework offers functional insights into gene-cell modules.
• CellSP facilitates discoveries in neuroscience and disease research.