scvelo
RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.
npx skills add LeonChaoX/qinyan-academic-skills --skill scvelo --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.
# 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:** `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 Use scVelo when: - **Trajectory inference from snapshot data**: Determine which direction cells are differentiating - **Cell fate prediction**: Identify progenitor cells and their downstream fates - **Driver gene identification**: Find genes whose dynamics best explain observed trajectories - **Developmental biology**: Model hematopoiesis, neurogenesis, epithelial-to-mesenchymal transitions - **Latent time estimation**: Order cells along a pseudot
- Overview
- When to Use This Skill
- Prerequisites
- Standard RNA Velocity Workflow
- 1. Setup and Data Loading
- 2. Preprocessing
- 3. Velocity Estimation — Stochastic Model
- 4. Velocity Estimation — Dynamical Model (Recommended)
- 5. Latent Time
- 6. Driver Gene Analysis
- 7. Velocity Arrows and Pseudotime
- 8. PAGA Trajectory Graph
- Complete Workflow Script
- Key Output Fields in AnnData
What does the scvelo skill do?
RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.
How do I install it?
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill scvelo --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 LeonChaoX/qinyan-academic-skills, a repository with 759 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.