🔬 SpatialScope
An interactive platform for spatial transcriptomics analysis. Draw freehand regions of interest directly on your tissue image, compare spatial domains, and perform statistical analyses — with no coding required.
✅ Accepts: Seurat object (.rds); 10x Visium SpaceRanger raw output
📖 Quick Start
💡 Tips & Best Practices
- Selection: Draw a region of interest using the freehand tool, then assign it to Group 1 or Group 2 for downstream comparison.
- Show Groups: Enable “Show Groups on Map” to visualize saved group selections overlaid on the tissue image.
- Species: Select the correct species (Human/Mouse) before using built-in gene signatures or pathway gene sets.
- Clustering: Start with the default resolution (0.8) and increase it for finer subgroup identification
- Export: Export selected ROIs as Seurat subsets for reuse in SpatialScope or downstream analysis in external tools.
🚀 Ready to Begin?
Click on the tools in the sidebar (🎨 Visualization, 🧬 Gene Sets, etc.) to start your spatial analysis. The tissue map will appear when you switch to any analysis tool.
Data Source
⚠️ Loading new data will replace current analysis
📋 How to prepare your zip:
- Locate your Space Ranger output folder
- Make sure all files are uncompressed (no .gz files)
- The folder must contain: .h5 file + spatial/ subfolder
- Compress the entire folder as a .zip and upload
Feature Selection
Color Scheme
🔗 L-R Colocalization Score
Compute ligand-receptor geometric mean scores in selected region.
Top L-R Pairs by Mean Score
🎨 Spots colored grey → red by ligand × receptor expression
Download LR Enrichment Table
🔬 Cell Type Deconvolution
Estimate cell type proportions in ROI using RCTD.
Reference Data
Additional references available at our GitHub Releases .
⚠️ Loading a new reference will reset deconvolution results.
💡 Save spots to Group 1 or Group 2 on the map first.
📚 Cell Marker Database
Pre-defined signatures are curated from CellMarker 2.0, a manually curated database of 26,915 cell markers across 2,578 cell types and 656 tissues.
Citation: Hu C, Li T, Xu Y, et al. Nucleic Acids Res. 2023;51(D1):D870-D876.
Species Selection
💡 Gene symbols will be updated based on species
Select Signature
💡 Select a pre-defined signature or enter custom genes below
Pathway Signatures (MSigDB Hallmark)
💡 Loads into Gene Input below — same scoring and visualization applies
Gene Input
Parameters
💡 Mean: Fastest, simple average
AddModuleScore: Fast, with control features
GSVA: Rank-based enrichment (may take 10-30s)
Color Legend
Spot Selection
💡 Tip: Save spots to Group 1 or Group 2 first using the map buttons
Parameters
Results
Group Information
💡 Tip: Use the group buttons at the bottom of the map to save selections and download spot IDs.
Analysis
⚠️ Clustering must be run first on the selected group
Top DEGs
💡 Tip: p_adj reflects differential expression; Moran's I (with adjusted p-values) quantifies spatial autocorrelation.
Download DEG Results