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Workflow Management in DNAWave

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Overview

DNAWave provides a powerful workflow management system that enables users to define, execute, and monitor genomic workflows. Workflows can be executed on Amazon Web Services (AWS) or on Google Cloud Platform (GCP), offering flexibility in cloud-based workflow execution.

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Creating a Workflow

To create a new workflow, navigate to the Workflow Creation Page and follow these steps:

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Required Fields:

• Name: A descriptive name for the workflow.
• Description: An overview of the workflow’s purpose and functionality.
• Engine: Choose between WDL (Workflow Description Language) or Nextflow for workflow scripting.
• Platform Type: Select AWS for cloud-based execution on AWS or GCP for Google Cloud-based execution.
• Definition URI: The storage path of the workflow definition file.
• Main: The entry script or primary definition file.
• Tags: Categorize workflows for easier retrieval.

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Workflow Configuration Options:

• Source Editor: Directly write or edit workflow scripts using the built-in code editor.
• ZIP File Upload: Upload a pre-packaged workflow definition as a .zip file.
• Parameter Template: Define JSON-based input parameters required for execution.
• Accelerators: Specify whether GPUs or specialized computing resources are needed.

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Viewing and Managing Workflows

Once a workflow is created, users can view and manage it from the Workflow View Page.

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Workflow Details Page

The Workflow View Page provides:

• Workflow metadata (Name, Description, Platform, Engine, Status, and Tags).
• Workflow definition details (Definition URI, Main file, Accelerators, Parameter Template).
• Linked Workflow Runs for monitoring execution history.
• Integration with dataset processing pipelines.
• AI-assisted workflow suggestions.

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Running a Workflow

DNAWave supports automated workflow execution:

• Create a Workflow Run: Initiate a new execution with user-defined parameters.
• Monitor Execution: Track real-time progress and resource utilization.
• Workflow Visualization: View a structured representation of workflow dependencies and execution paths.
• Workflow Status: Check execution logs, errors, and final results.

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Workflow Versioning

Users can track workflow modifications with Workflow Version History:

• Each version logs changes, including timestamps and modification reasons.
• Users can compare previous versions with the latest updates.
• Versions are linked to the user responsible for changes.

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API Integration

Developers can automate workflow management using the DNAWave REST API:

• Create, update, and delete workflows.
• Retrieve workflow metadata and execution logs.
• Execute workflows programmatically.

Refer to the API Documentation for further details.

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Summary

The DNAWave Workflow Management System simplifies genomic workflow execution with powerful automation, cloud integration, and AI-powered insights. Get started today to enhance your research efficiency!