This pathway will walk you through how to upload your study data into the Fred Hutch instance of cBioPortal.

Glossary of terms used in this article:

  • HutchNet ID A user ID specific to the Fred Hutch.

  • VPN A Virtual Private Network that allows secure access to the Fred Hutch network from off-campus.

  • AWS Amazon Web Services – a cloud platform used to store and access research data and tools.

  • S3 Amazon S3 (Simple Storage Service) is a cloud-based object storage service used to store and retrieve data.

  • Workflow manager Software that coordinates the submission of jobs, inputs and outputs of individual jobs in a scientific workflow.

  • IRB Institutional Review Board – a committee that reviews and approves research involving human subjects to ensure ethical standards are met.

Pre-requisites

  • You must have a HutchNet ID and access to the Fred Hutch network
  • IRB approval for the study you wish to upload (if applicable)

Step 1: Request Upload Access

To upload a study to the Fred Hutch cBioPortal instance you need to fill out the Access Request Form.

Once your study upload request is approved, the Data Governance & Protection team will reach out to you to confirm

Step 2: Set Up AWS Credentials

Once approved you will need to make sure your team has a Fred Hutch AWS lab account. And all individuals on your team that have been approved to upload data are setup under the lab/team account with their individual AWS credentials.

📝 Note: You can test your credentials by following these steps.

Step 3: Get Access to the S3 Bucket

Once credentials are working:

  • Contact the cBioPortal team on Slack via #cbioportal-support
  • You’ll be given write-only access to the fh-dasl-cbio bucket

📝 Note: Make sure to test your access using aws s3 cp or try uploading via Motuz.

Step 4: Prepare Your Files

Data must be formatted following cBioPortal data structure. We also provide Fred Hutch-specific guides and examples.

Minimum required files:

  • meta_study.txt
  • meta_clinical_sample.txt and data_clinical_sample.txt
  • case_lists/cases_sequenced.txt

Step 5: Upload Your Study

Once formatted, compress your study folder:

cd /path/to/folder
zip -r cancer_study_identifier.zip cancer_study_identifier

Then upload using one of the following methods:

  • Motuz: Upload via motuz.fredhutch.org
  • Mountain Duck: Mount fh-dasl-cbio as a drive and drag/drop
  • Command Line: begin by configuring the AWS CLI and upload via the following command 
    aws s3 cp cancer_study_identifier.zip s3://fh-dasl-cbio/

Once uploaded, an automated pipeline will validate and load your data.

📝 Note: You’ll receive a validation email. If there are errors, it will include details in an attached report.

Where to Go From Here

Need Help?

↩️ Back to: What is cBioPortal?

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