---
title: "Single-cell RNA Sequencing — Instructions"
canonical: "https://build.nvidia.com/playbooks/single-cell/instructions.md"
---

# Step 1. Verify your environment

Let's first verify that you have a working GPU, git, and Docker.  Open up Terminal, then copy and paste in the below commands:

```bash
nvidia-smi
git --version
docker --version
```

- `nvidia-smi` will output information about your GPU.  If it doesn't, your GPU is not properly configured.
- `git --version` will print something like `git version 2.43.0`.  If you get an error saying that git is not installed, please reinstall it.
- `docker --version` will print something like `Docker version 28.3.3, build 980b856`.  If you get an error saying that Docker is not installed, please reinstall it. If you see a permission denied error, add your user to the docker group by running `sudo usermod -aG docker $USER && newgrp docker`.

# Step 2. Installation
Open up Terminal, then copy and paste in the below commands:

```bash
git clone https://github.com/NVIDIA/dgx-spark-playbooks
cd dgx-spark-playbooks/nvidia/single-cell/assets
bash ./setup/start_playbook.sh
```

start_playbook.sh will:

1. pull the RAPIDS 25.10 Notebooks Docker container
2. build all the environments needed for the playbook in the container using setup_playbook.sh
3. start JupyterLab

Please keep the Terminal window open while using the playbook.

You can access your JupyterLab server in two ways
1. at `http://127.0.0.1:8888` if running locally on the DGX Spark. 
2. at `http://<SPARK_IP>:8888` if using your DGX Spark headless over your network.

Once in JupyterLab, you'll be greeted with a directory containing scRNA_analysis_preprocessing.ipynb, and the folders `cuDF`, `cuML`, `cuGraph`, and `playbook`. 

- `scRNA_analysis_preprocessing.ipynb`is the playbook notebook.  You will want to open this by double clicking on the file.
- `cuDF`, `cuML`, `cuGraph` folders contain the standard RAPIDS library example notebooks to help you continue exploring.
- `playbook` contains the playbook files.  The contents of this folder are read-only inside of a rootless Docker Container.

If you want to install any of the playbook notebooks on your own system, check out the readmes within the folder that accompanies the notebook

# Step 3. Run the notebook

Once in JupyterLab, there all you have to do is run the `scRNA_analysis_preprocessing.ipynb`. You'll get both these playbook notebooks as well as the standard RAPIDS library example notebooks to help you get going.

You can use `Shift + Enter` to manually run each cell at your own pace, or `Run > Run All` to run all the cells.

Once you're done with exploring the `scRNA_analysis_preprocessing` notebook, you can explore other RAPIDS notebooks by going into the folders, selecting other notebooks, and doing the same thing.

# Step 4. Download your work

Since the docker container cannot privileged write back to the host system, you can use JupyterLab to download any files you may want to keep once the docker container is shut down.

Simply right click the file you want, in the browser, and click `Download` in the dropdown.

# Step 5. Cleanup

Once you have downloaded all your work, go back to the Terminal window where you started running the playbook.

In the Terminal window, 
1. Type `Ctrl + C`
2. Quickly either enter `y` and then hit `Enter` at the prompt or hit `Ctrl + C` again
3. The Docker container will proceed to shut down

> [!WARNING]
> This will delete ALL data that wasn't already downloaded from the Docker container.  The browser window may still show cached files if it is still open.