Spatial Omics Skills Index
Skills for spatial transcriptomics analysis including single-cell to spatial mapping (MOSCOT), 3D visualization (PyVista), and related spatial workflows.
npx skills add BioTender-max/awesome-bio-agent-skills --skill spatial --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Spatial Omics Skills Skills for spatial transcriptomics data analysis, mapping, and visualization. ## Available Skills ### Single-Cell to Spatial Mapping Map scRNA-seq to spatial data using optimal transport (MOSCOT) for gene imputation and cell type transfer. **Skill file**: [single_cell_spatial_mapping.md](./single_cell_spatial_mapping.md) **When to use**: - You have paired scRNA-seq and spatial transcriptomics data - You want to impute genes not measured in the spatial modality - You want to transfer cell type annotations to spatial coordinates ### 3D Spatial Data Visualization Interactive 3D visualization and rotating GIF animations for spatial data with PyVista. **Skill file**: [visualize_3d_spatial.md](./visualize_3d_spatial.md) **When to use**: - Your spatial data has 3D coordinates - You want to visualize gene expression or cell types in 3D - You want to create rotating GIF animations ### Spatial 3D Slice Alignment (Spateo) Align serial spatial transcriptomics sections into a 3D volume using Spateo morpho_align with pairwise rigid registration. **Skill file**: [spatial_3d_alignment.md](./spatial_3d_alignment.md) **When to use**: - You have serial tissue sections that need
- Available Skills
- Single-Cell to Spatial Mapping
- 3D Spatial Data Visualization
- Spatial 3D Slice Alignment (Spateo)
- Spatial Cell-Cell Interaction (Spateo LR)
- Spatial Deconvolution (Cell2location / Tangram)
- Spatial Signal Boundary Analysis
- Serial H&E Image Registration (RoMa)
What does the Spatial Omics Skills Index skill do?
Skills for spatial transcriptomics analysis including single-cell to spatial mapping (MOSCOT), 3D visualization (PyVista), and related spatial workflows.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill spatial --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.