Notebooks

The interactive analysis environment of Bio-OS integrates Jupyter Notebook. Jupyter Notebook is a shareable and reproducible interactive analysis environment.

Jupyter Notebook is an open-source analysis environment where you can perform interactive analyses and visualizations to explore research data in real time. You can import data—including processed genomics, phenotypic, and transcriptomics datasets stored in the cloud—and analyze them using custom or prebuilt libraries in R or Python.

The Jupyter Notebook environment is beginner-friendly, portable, and reproducible. It combines analytical methods and research findings in a single, easy-to-understand, and shareable format. As a logical evolution of the traditional scientific paper, Jupyter Notebook dramatically shortens the distance between understanding how an analysis was conducted and actually reproducing it. The power of this concept, and its impact on reusability and reproducibility in computational science, can hardly be overstated.

Switch configuration

The Notebook supports switching runtime resources, allowing you to modify both application and resource configurations. The application configuration mainly specifies the default image to launch, while the resource configuration allows you to select the desired resource specifications.

1. Click Run Resource Configuration

2. Select the application configuration and resource configuration

3. Click Update Environment (if the current Notebook instance is already running, clicking Update Environment will delete the instance and restart it).

Application configuration

A preset image is currently available: datascience. The datascience image is the base image provided by the platform and includes a set of commonly used data science tools.

Resource configuration

By default, two types of resource configurations are provided: minimal resources (1-core CPU, 1 GB memory) and default resources (2-core CPU, 4 GB memory). You may also modify the configuration file as needed to customize resource settings. When a Notebook is launched, it will request the corresponding resource allocation from the cluster.

Create Notebook

1. Click New Notebook, enter a name, and select a language. Currently, Python and R are supported.

1. Click the Edit button on the right to edit the Notebook.

1. There are three ways to run a code cell in a Notebook:

   1. Select the cell and press Shift + Enter on the keyboard (your keyboard may display Return instead of Enter).

   2. Click the Run icon in the menu bar.

   3. Use the appropriate command from the Cell dropdown menu.

A cell line is a fundamental component of a Notebook. Each cell has a type (Code / Markdown / Raw), which determines how the application interprets the instructions within the cell during computation.