The All of Us Researcher Workbench supports a variety of cloud-based applications to analyze All of Us participant data, including JupyterLab, RStudio (R Analysis Environment), and SAS Studio (AoU SAS). The platform also supports tools to manage computational workflows (Cromwell, Nextflow and dsub).
These applications run on cloud compute resources within your workspace and incur costs based on usage. Cloud resources are virtual computing environments that allow you to access and manage analysis tools and data over the internet. All compute and storage costs are billed through your selected billing pod. Read what to know about costs and how to pay for research analysis.
JupyterLab
JupyterLab is an interactive analysis environment which provides a flexible interface where researchers can write and execute code, visualize data, and manage files.
Within JupyterLab, you can create and work with Jupyter notebooks, which are documents that combine code, outputs, visualizations, and narrative text in a single, shareable file. You can use Jupyter Notebooks to:
- Run analyses in Python, R, or SQL
- Explore and visualize datasets
- Document your research workflows
Researcher Workbench also offers multiple JupyterLab-based environments, including:
- JupyterLab for general-purpose analysis
- Spark-enabled JupyterLab for large-scale data processing
- NVIDIA-enabled environments for GPU-accelerated workflows
- Please note: NVIDIA environments are resource‑intensive and can incur significant computational costs. Be sure to review the associated expenses and confirm appropriate cloud resource allocations before provisioning these environments.
Resources for Jupyter Notebook
R Analysis Environment (RStudio)
RStudio is available as R Analysis Environment, which runs on cloud compute resources within your workspace.
It provides an integrated development environment (IDE) for researchers working with the R programming language, making it easier to write, debug, and execute R code. RStudio is commonly used for statistical analysis, data visualization, and reproducible research workflows.
Resources for RStudio
SAS Studio
SAS Studio (available as AoU SAS) is a statistical software tool used by researchers for data analysis and statistical modeling. SAS Studio has the ability to handle large datasets efficiently with an extensive set of statistical techniques and a user-friendly interface. Programming language SAS is available for SAS Studio in the Researcher Workbench.
Workflows
Workflows in the Researcher Workbench enable you to automate and run multi-step computational analyses at scale (for example, running the same pipeline across many samples or parameter sets).
The Researcher Workbench currently supports running workflows using Cromwell, Nextflow, and dsub. These are external workflow tools (not tools developed by the All of Us Research Program) that run on Google Cloud compute resources in your workspace.
- Cromwell is an open-source workflow management system that is designed to help scientists and researchers organize and execute complex computational workflows written in WDL (Workflow Description Language). Cromwell provides a platform for defining, running, and monitoring workflows, making it easier to manage and automate scientific analyses. Cromwell application can be launched from the workspace analysis panel.
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Nextflow is an open-source flexible workflow engine that uses a domain-specific language (DSL based on Groovy) to orchestrate scalable and reproducible pipelines across compute environments. It is widely used for data-intensive and parallel processing workflows.
- dsub is an open-source, command-line workflow tool designed to run batch jobs on Google Cloud. It allows you to execute scripts and pipelines in parallel across cloud resources, making it well-suited for large-scale data processing tasks.
Resources for Workflows
For examples of how to use workflow tools in the Researcher Workbench, please see our Featured Workspaces linked below, which include tutorial workspaces that you can copy and adapt for your research.
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