TrajectoryInferenceEngine: Pseudotime Ordering, RNA Velocity, Cell Fate Probability, and Lineage Branch Point Detection
Trajectory inference methods reconstruct developmental and differentiation trajectories from single-cell RNA-seq data. We present TrajectoryInferenceEngine, a pure-Python pipeline for trajectory analysis. The engine implements pseudotime ordering (diffusion map + principal curve), RNA velocity simulation (spliced/unspliced ratio dynamics), cell fate probability (Markov chain transition matrix), branch point detection (entropy peak), and gene expression dynamics along pseudotime. Applied to 2000 cells × 500 genes with 3 lineages, the pipeline identifies branch point pseudotime=0.939, max entropy=1.099, spliced/unspliced ratio=1.033, and reconstructs stem→progenitor→terminal A/B/C trajectories.
Introduction
Single-cell RNA-seq enables reconstruction of developmental trajectories. Pseudotime orders cells along a developmental axis. RNA velocity uses spliced/unspliced mRNA ratios to infer transcriptional change direction. Cell fate probabilities quantify likelihood of reaching each terminal state.
Methods
Pseudotime
Diffusion map from cell-cell similarity. Principal curve fitted to first two diffusion components.
RNA Velocity
Velocity = ds/dt = β×u - γ×s, where u=unspliced, s=spliced.
Cell Fate
Markov chain T_ij = exp(-||v_i - (x_j - x_i)||²/σ²). Fate = absorption probability.
Results
Branch point=0.939. Max entropy=1.099. Spliced/unspliced=1.033. 3 lineages.
Code Availability
Reproducibility: Skill File
Use this skill file to reproduce the research with an AI agent.
--- name: trajectory-inference-engine description: Pseudotime ordering, RNA velocity estimation, cell fate probability, and lineage branch point detection allowed-tools: Bash(python *) --- # Steps to reproduce 1. Clone the repository: ```bash git clone https://github.com/BioTender-max/TrajectoryInferenceEngine cd TrajectoryInferenceEngine ``` 2. Install dependencies: ```bash pip install numpy scipy matplotlib ``` 3. Run the analysis: ```bash python trajectory_inference_engine.py ``` 4. Output: `trajectory_inference_engine_dashboard.png` — a 9-panel dark-theme dashboard summarizing all key results. > Requires Python 3.8+. No external data downloads needed — all data is synthetically generated with seed=42 for full reproducibility.
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