Getting Started with Arvados
What you're looking at right now is Workbench, the graphical interface to the Arvados system.
Running the Pathomap pipeline in Arvados.
Click the Next > button below for a speed tour of Arvados.
Note: You can always come back to this Getting Started guide by clicking the in the upper-right corner.
Run your first pipeline in 3 quick steps:
First, log-in or register with any Google account if you haven't already.
- Go to the Dashboard > Run a pipeline...
- Mason Lab -- Ancestry Mapper (public) > Next: choose inputs
- Run
Voila! Your pipeline is now spooling up and getting ready to run!
Go ahead, try it for yourself right now.
Or click Next > below to keep reading!
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Pipeline — A re-usable series of analysis steps.
- Also known as a “workflow” in other systems
- A list of well-documented public pipelines can be found in the upper right corner by clicking the > Public Pipelines and Datasets
- Pro-tip: A Pipeline contains Jobs which contain Tasks
- Pipelines can only be shared within a project
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Collection — Like a folder, but better.
- Upload data right in your browser
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Better than a folder?
- Collections contain the content-address of the data instead of the data itself
- Sets of data can be flexibly defined and re-defined without duplicating data
- Collections can be shared using the "Sharing and Permissions" > "Share" button
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Projects — Contain pipelines templates, pipeline instances (individual runs of a pipeline), and collections.
- The most useful one is your default "Home" project, under Projects > Home
- Projects can be shared using the "sharing" tab
This guide, and in fact all of Workbench, is just a teaser for the full power of Arvados:
- Reproducible analyses: Enough said.
- Data provenance: Every file in Arvados can tell you where it came from.
- Serious scaling: Need 500 GB of space? 200 compute hours? Arvados scales and parallelizes your work for you intelligently.
- Share pipelines or data: Easily publish your work to the world, just like the Pathomap team did.
- Use existing pipelines: Use best-practices pipelines on your own data with the click of a button.
- Open source: Arvados is completely open source. Check out our developer site.
Want to use the command-line, or hungry to learn more? Check out the User Guide at doc.arvados.org.
Questions still? Head over to doc.arvados.org to find mailing-list and contact info for the Arvados community.
That's all, folks! Click the "x" up top to leave this guide.
| Name | Description |
|---|---|
| TensorFlow demo |
This is the corresponding Arvados project for this blog post about GPUs in Arvados. |
| Alphafold demo | |
| Alphafold parameters | |
| resources | |
| Debugging Blog post data and examples | |
| testhub | |
| VeggieDB | |
| Digital Pathology | |
| Imaging Flow Cytometry | |
| Labelbox | |
| Kallisto RNA-seq example | |
| CWL Training reference data | |
| Lukasa test | |
| Public favorites |
Public favorites |
| WGS Processing Workflow |
This project contains an example whole genome sequencing (WGS) workflow and its accompanying scripts, reference data, and Docker container images required to run it. You can learn more and run this workflow yourself by going through the Processing Whole Genome Sequences walkthough in the user guide. |
| Sample data |
Sample input data for the WGS processing example. |
| Tutorial projects |
Projects containing collections and workflows referenced in the Arvados User Guide |
| Workflow Runs |
Provenance records of the workflow steps of the WGS processing example run. |
| User guide resources |
This contains files for the Starting a Workflow at the Command Line and Using arv-copy sections of the Arvados User Guide. |