Getting Help

The JAWS team is committed to supporting your research. This page explains how to get help, report issues, and engage with the community.

Quick Help Channels

💬 Slack (fastest)

Best for: quick questions, real-time discussions

Join #jaws at joint-genome-inst.slack.com

  • Quick responses during business hours.

  • Share screenshots, logs, WDL snippets.

  • Community-supported (other users may help too).

  • Search past conversations for answers.

📧 Email Support

Best for: external collaborators without Slack access

Send to: jaws-support@lbl.gov

  • Attach logs, screenshots, WDL files.

  • For users without JGI GitLab access.

🎟️ GitLab Issues

Best for: bug reports, feature requests

Create issues at jaws-support repo.

  • Requires JGI Staff access (request via Slack if needed).

  • Track progress on the public roadmap.

  • Vote on features you need (see “Voting on Features” below).

👥 Pair Programming

Best for: workflow development, debugging sessions

To request a session, post in #jaws or email jaws-support@lbl.gov.

  • Bring your WDL draft or problem description.

  • Collaborative problem-solving with a JAWS engineer.

Reporting Issues

When you encounter a problem, follow these steps to get the fastest resolution.

Before Reporting

  1. Check existing resources:

  2. Gather diagnostic information:

    # Get full workflow status
    jaws status RUN_ID --verbose > status.txt
    
    # Export lifecycle log
    jaws log RUN_ID > logs.txt
    
    # Per-task table (status, cached flag, return codes)
    jaws tasks RUN_ID > tasks.txt
    

    For task-level error output, look at the stderr and stdout files in the Cromwell execution directory of the failed task. To pull them back from a remote compute site, run jaws download RUN_ID.

Creating a GitLab Issue

  1. Go to jaws-support.

  2. Click “New issue”.

  3. Choose template: “Bug Report”.

  4. Fill in:

    ## Bug Description
    [Clear description of unexpected behavior]
    
    ## Steps to Reproduce
    1. Run workflow: `jaws submit my_workflow.wdl inputs.json <site>`
    2. Observe error in task: `align_reads`
    3. Error message: "OutOfMemoryError"
    
    ## Expected Behavior
    Task should complete successfully with 32GB RAM.
    
    ## Logs
    [Attach jaws log output or link to files]
    
  5. Add label: user_request (critical!).

  6. Add label: bug::bug.

  7. Click “Submit issue”.

  1. Go to jaws-support.

  2. Click “New issue”.

  3. Choose template: “Feature Request”.

  4. Fill in:

    ## Feature Description
    [What capability do you need?]
    
    ## Use Case
    I am working on [X] and need to [Y] because [Z].
    
    ## Proposed Solution
    [How would this work? Mock CLI commands, WDL syntax, etc.]
    
    ## Alternatives Considered
    [What workarounds have you tried?]
    
    ## Priority
    [How critical is this for your research?]
    
  5. Add label: user_request (critical!).

  6. Click “Submit issue”.

Important

Always add the user_request label!

This label:

  • Triggers notifications to the JAWS team.

  • Displays your issue on our triage board.

  • Ensures a timely response (we may miss unlabeled issues).

Voting on Features

JAWS development is community-driven. You can influence our roadmap by voting on features you’d like to see.

How to Vote

  1. Browse the Issue Board.

  2. Find issues labeled user_request that match what you need.

  3. Open the issue and, in the right-hand panel, increase the Weight field by 1. Weight is GitLab’s built-in issue priority field; bumping it signals user demand, and we use it to reorder the backlog. The updated weight appears on the board immediately.

  4. Add a comment describing your specific use case. The comment is often more important than the +1: it helps us understand impact.

Voting Guidelines

  • Vote on up to 3 issues at a time — your top priorities.

  • Comment with your specific use case so we can weigh impact.

  • Check back periodically; we reprioritize regularly based on accumulated weight and comments.

Pair Programming Sessions

Schedule a personalized workflow development session with a JAWS engineer. Best for working through tricky WDL design, debugging a stuck pipeline, or learning by doing on a real workflow of yours.

How to Schedule

Post in #jaws or email jaws-support@lbl.gov with a brief description of what you’d like to work on. We’ll coordinate a Zoom time that fits both schedules.

JAWS Community

Office Hours

The JAWS team runs regular drop-in office hours over Zoom. The current schedule lives on the JAWS Events calendar — times shift occasionally and the calendar is the source of truth.

Bring questions about your workflows, your WDLs, errors you’re seeing, or anything else. No agenda needed; drop in.

Workshops and Training

To request a workshop, training session, or pair-programming session for your team, post in #jaws or email jaws-support@lbl.gov. We can tailor sessions to your team’s needs.

The JAWS Events calendar lists upcoming sessions. Past workshop materials live in Workshops Archive.

JAWS Team

Meet the people behind JAWS.

Current Team Members

  • Daniela Cassol

  • Mario Melara

  • Nick Tyler

  • Ramani Kothadia

  • Ludovico Bianchi

  • Joshua Boverhof

  • Seung-jin Sul

  • Setareh Sarrafan

  • Kjiersten Fagnan

Past Contributors

We’re grateful to former team members who built JAWS:

  • Steve Chan

  • Jeff Froula

  • Edward Kirton

  • Stephan Trong

  • Georg Rath

  • Angie Kollmer

  • Kelly Rowland

  • Elais Player

External Resources

Learn more about the technologies behind JAWS:

📖 WDL 1.0 Specification

The WDL spec JAWS supports today. (WDL 1.1 is not yet supported — see the FAQ for details.)

🔧 Cromwell Docs

The Broad Institute’s workflow engine, which JAWS uses under the hood.

💻 WDL Tutorials (Terra)

Terra’s WDL learning materials. Note: Terra is GCP-centric; some examples won’t directly translate to JAWS’ HPC backends, but the WDL syntax is the same.

Still Have Questions?

If you didn’t find what you needed:

We’re here to help

No question is too basic. Our goal is to make JAWS accessible to all researchers, regardless of computational background.

See also

Related pages