GeneSurfer Enables Transcriptome-wide Exploration and Functional Annotation of Gene Co-expression Modules in 3D...

Area of Science:

• Computational Biology
• Genomics
• Bioinformatics

Background:

• Gene co-expression analysis is vital for understanding biological functions.
• Existing tools lack capabilities for localized co-expression exploration in large datasets.

Purpose of the Study:

• To introduce GeneSurfer, an interactive interface for exploring localized transcriptome-wide gene co-expression patterns in the 3D spatial domain.
• To provide a tool that facilitates the identification and annotation of spatially resolved gene expression patterns.

Main Methods:

• Developed GeneSurfer, an interactive interface with features for gene filtering, spatial clustering, and 3D visualization.
• Integrated on-the-fly Gene Ontology (GO) term annotation for co-expressed gene sets.
• Applied the tool to spatial transcriptomics and single-cell RNA sequencing data from the Allen Brain Cell Atlas.

Main Results:

• GeneSurfer enables efficient exploration of localized gene co-expression in 3D spatial data.
• The tool successfully identified and annotated localized transcriptome-wide co-expression patterns.
• Demonstrated utility in generating biological insights and facilitating hypothesis generation.

Conclusions:

• GeneSurfer addresses the need for exploratory analysis tools for localized gene co-expression.
• The interface enhances the investigation of spatial transcriptomic data.
• Facilitates deeper understanding of gene function and regulation within spatial contexts.