Individual skill
scvelo
Performs RNA velocity analysis with scVelo on single-cell RNA-seq AnnData objects that have spliced and unspliced layers (from velocyto, STARsolo, kallisto|bustools, or alevin-fry). Covers stochastic and dynamical velocity models, velocity graphs and embedding arrows, latent time, PAGA trajectory graphs, and driver gene ranking. Use when inferring differentiation direction from snapshot data, estimating latent time from splicing kinetics, finding driver genes of a trajectory, or adding velocity arrows to a Scanpy UMAP. Not for fate probability modeling (use CellRank) or datasets without unspliced counts.
plugins/KalarisLabs/research-agent-skills/skills/scvelo/SKILL.md
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- Last checked
- Nov 4, 2026
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- Nov 6, 2026
- License
- Apache-2.0
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- rna-velocity,-single-cell,-cell-trajectories,-transcriptomics Declared skill tag
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# scVelo — RNA Velocity Analysis
## Overview
scVelo is the leading Python package for RNA velocity analysis in single-cell RNA-seq data. It infers cell state transitions by modeling the kinetics of mRNA splicing — using the ratio of unspliced (pre-mRNA) to spliced (mature mRNA) abundances to determine whether a gene is being upregulated or downregulated in each cell. This allows reconstruction of developmental trajectories and identification of cell fate decisions without requiring time-course data.
**Installation:** `uv pip install scvelo`
**Key resources:**
- Documentation: https://scvelo.readthedocs.io/
- GitHub: https://github.com/theislab/scvelo
- Paper: Bergen et al. (2020) Nature Biotechnology. PMID: 32747759
## When to Use This Skill