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.

.. toctree::
   :maxdepth: 1
   :caption: Simulated SDE demo

   demo_simulation

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.