STtools

STtools processes ultra-high-resolution spatial transcriptomics data to enable computational analysis and visualization of spatial gene expression from sub-micrometer Seq-Scope to 100-micrometer VISIUM datasets.

Key Features:

• Sequencing platform support: Handles data from Seq-Scope (<1‑micrometer resolution), Slide‑seq (10‑micrometer resolution), and VISIUM (100‑micrometer resolution).
• Raw FASTQ processing: Processes raw FASTQ files directly for integration into downstream analyses.
• Adaptable resolution framework: Provides an adaptable framework for processing spatial transcriptomics data across a range of resolutions and scales while maintaining scalability.
• High-resolution downstream analyses: Performs downstream analyses at resolutions significantly higher than those achievable with current methods to resolve fine spatial expression patterns.
• Transcriptome Density Mapping: Produces visual representations of gene expression density across tissue regions.
• Cell Type Mapping: Identifies and maps cell types based on transcriptomic profiles.
• Marker Gene Highlighting: Highlights specific marker genes for defined cell types or states.
• Subcellular Architectures: Visualizes spatial arrangements at subcellular resolution.

Scientific Applications:

• Spatial gene expression analysis: Resolves spatial organization and expression patterns within tissues across multiple resolution scales.
• Cell type and tissue architecture characterization: Maps and classifies cell types and their spatial distributions in tissue contexts.
• Subcellular localization studies: Investigates subcellular architectures and spatial arrangements of transcripts.
• Systems biology and disease mechanism investigation: Supports analyses in genomics, transcriptomics, and systems biology to study complex biological processes and disease mechanisms.

Methodology:

Processes raw FASTQ files and performs downstream analyses at sub-micrometer to 100‑micrometer resolutions, generating transcriptome density maps, cell type maps, marker gene highlighting, and subcellular architecture visualizations.