scCS — Single-Cell Commitment Scores¶
Contents
- Introduction
- Mathematical Framework
- Requirements
- scCS Tutorial — Single-Condition Analysis
- Single-cell Commitment Scores with Radial Star Embedding
- 1. Installation
- 2. Load & preprocess data
- 3. RNA velocity
- 4. Build the radial star embedding
- 5. Fix arm coverage with subset-local pseudotime
- 6. Fit and compute commitment scores
- 7. Visualizations
- 8. Per-cell fate affinity scores
- 9. Transfer labels to full adata
- 10. Subset scoring
- 11. Driver genes
- 12. Pathway enrichment
- 13. Expression trends along fate arms
- Summary — scCS single-condition workflow
- scCS Tutorial — Pairwise Condition Comparison
- Multi-Condition Commitment Score Analysis with
PairScorer - 1. Setup and data loading
- 2. Create artificial condition split
- 3. Initialize
PairScorer - 4. Build the shared star embedding
- 5. Fit the shared FateMap
- Tier 1: Score each condition on the shared embedding
- Tier 2: Statistical comparison
- Tier 3: Trajectory-level analysis
- 6. Driver genes per condition
- 7. Pathway enrichment per condition
- 8. Expression trends along fate arms — per condition
- 9. Transfer labels to full adata
- Summary — scCS pairwise workflow
- Multi-Condition Commitment Score Analysis with
- scCS Tutorial — Multi-Condition Analysis with
MultiScorer - scCS Benchmark Tutorial — Processing Speed Scaling
- API Reference
- Changelog
- API Reference