Simulation Tutorial

This tutorial demonstrates the application of SDEvelo to simulated single-cell RNA sequencing (scRNA-seq) data. By following this guide, you will learn how to generate synthetic data, apply SDEvelo to model transcriptional dynamics, and analyze the results in comparison to the known ground truth.

Contents

In this tutorial, you will:

1. Generate Simulated scRNA-seq Data

2. Apply SDEvelo to Model Transcriptional Dynamics

3. Analyze and Compare Results to Ground Truth

Getting Started

To follow along with this tutorial, ensure you have SDEvelo installed.

Note

It’s recommended to use a virtual environment to manage dependencies and avoid conflicts.

Tutorial Notebook

The core of this tutorial is a Jupyter notebook that guides you through each step interactively.

Simulated SDE demo

• Generate SDE-based simulation data
• Train SDEvelo model
• Visualization

How to Use This Tutorial

1. Open the Notebook: Navigate to the demo_simulation.ipynb notebook in this section and open it using Jupyter Notebook or JupyterLab.

2. Follow the Instructions: Each section of the notebook contains detailed explanations and code snippets. Execute the cells sequentially to replicate the simulation and analysis.

3. Explore and Modify: Feel free to experiment by modifying parameters or adding new analyses to deepen your understanding of SDEvelo’s capabilities.

Expected Outcomes

By the end of this tutorial, you will:

• Understand how to generate realistic simulated scRNA-seq data.

• Gain hands-on experience applying SDEvelo to model transcriptional dynamics.

• Be able to interpret the results and assess the accuracy of the modeling against known ground truth.