spVelo (Long et al., Genome Biology 2025)
Long, Liu, Xue & Zhao. Genome Biology 26:239 (2025). Penn State / Yale.
Summary
spVelo extends the veloVI Bayesian deep-generative model to multi-batch spatial transcriptomics: a VAE with two orthogonal encoders — an MLP on (unspliced, spliced) expression and a Graph Attention Network (GAT) on spatial location — fused in latent space, with a Maximum Mean Discrepancy (MMD) penalty across batches for batch-effect correction. It infers per-gene kinetics, a per-cell latent time, and supports uncertainty, trajectory discovery, driver markers, GRN, and temporal cell–cell communication. For the wiki it is a spatial sibling of TopoVelo — but a revealing contrast: spVelo uses spatial info for batch correction and neighbor structure, not to recover physical migration velocity, so it stays ordinal where TopoVelo reaches μm/hour.
Key Claims
- veloVI-based model. Per-gene transcription/splicing/degradation rates, latent transcriptional state, and per-gene latent times tied via a shared low-dimensional latent variable (veloVI assumptions), fit by variational inference.
- Spatial + multi-batch. GAT encodes spatial proximity; MMD aligns batch latent spaces — the first to do velocity across multiple spatial batches (prior methods are per-batch).
- Spatial info helps. Ablation shows integrating spatial location improves velocity + trajectory inference; spVelo’s direction score ranks highest vs scVelo, veloVI, LatentVelo on simulated pancreas + real OSCC.
- Downstream. Uncertainty, complex (non-linear) trajectory discovery, state driver markers, GRN, and temporal cell–cell communication.
Physical-time grounding (standing lens)
- Latent time — ordinal or metric? Ordinal (veloVI-style per-cell latent time); validated by direction/transition scores. No physical units.
- Scale degeneracy. Inherited (veloVI-relative); no absolute anchor.
- External time anchor. None — and this is the key contrast with TopoVelo: spVelo uses spatial coordinates for batch correction + GAT neighbor structure, not to derive a physical-unit migration velocity. Spatial context ≠ spatial velocity here.
- Constant-rate assumptions. Per-gene constant β, γ (veloVI); α per-state. Spatial coupling does not relax rate constancy.
Useful for the spatial-axis story (spatial-velocity): “spatial” methods split into those that merely use space as context/batch structure (spVelo) and those that recover physical migration velocity (TopoVelo). Only the latter touches physical units — and even then by assumption (see physical-time-grounding).
Connections
- spVelo — the method entity (upgraded from bookmark-only).
- veloVI — the model it extends.
- TopoVelo / spatial-velocity — spatial sibling; the physical-units contrast.
- latent-time / physical-time-grounding — ordinal, scale-relative.
- velocity-discourse-2025-2026 — bookmarked there.
- FlowVelo — clarifies “spatial context” vs “spatial velocity” as distinct claims.
Contradictions
- None. Replaces the bookmark-only stub; sharpens the spatial-axis taxonomy on spatial-velocity.