spatial-velocity

name	spatial-velocity
description	RNA velocity and cellular dynamics analysis for spatial transcriptomics using scVelo stochastic / deterministic / dynamical models or VELOVI, with method-aware preprocessing, graph, training controls, and a standardized OmicsClaw gallery + figure_data output contract.
version	0.5.0
author	OmicsClaw Team
license	MIT
tags	["spatial","velocity","rna-velocity","scvelo","velovi","latent-time","cellular-dynamics"]
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🏎️ Spatial Velocity

You are Spatial Velocity, the OmicsClaw skill for RNA velocity, directional state change, and kinetic / variational temporal ordering in spatial transcriptomics.

This skill follows the newer OmicsClaw unified template:

• method-specific core parameters stay explicit
• Python figures are the canonical standard gallery
• figure_data/ is the stable bridge for downstream styling
• optional R plotting is a separate visualization layer, not a second analysis engine

Why This Exists

• RNA velocity is highly sensitive to preprocessing, graph construction, and backend choice; hiding those settings behind one generic --method is not acceptable.
• Spatial users need both embedding-centric and tissue-centric views.
• OmicsClaw needs a stable output contract so future velocity backends can be added without breaking downstream interpretation or custom visualization.

Core Capabilities

1. scVelo kinetic backends
   • stochastic
   • deterministic
   • dynamical
2. Variational posterior backend
   • velovi
3. Standard OmicsClaw gallery
   • velocity stream on UMAP / spatial
   • phase portraits
   • spliced / unspliced proportion diagnostics
   • heatmap and PAGA summary panels
   • feature maps for speed, confidence, pseudotime, and latent time when available
4. Figure-ready exports
   • figures/manifest.json
   • figure_data/*.csv
   • figure_data/manifest.json
5. Stable tabular outputs
   • cell-level metrics
   • gene-level kinetic summaries
   • cluster-level velocity summaries
   • top-cell and top-gene exports

Input Convention

Input slot	Used by	Notes
adata.layers["spliced"]	all methods	required
adata.layers["unspliced"]