dnanexus-integration

Integrate with DNAnexus using the dxpy Python SDK for genomics workflows.

Updated Dec 17, 2025

Search Tags:#workflow #data management #genomics #python sdk #dnanexus

Ready to run

npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill dnanexus-integration-robotlearning123

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dnanexus-integration
Source: https://github.com/robotlearning123/claude-scientific-skills/tree/main/scientific-skills/dnanexus-integration
Command: npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill dnanexus-integration-robotlearning123

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires dxpy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the use of DNAnexus, a cloud platform for genomics, allowing users to manage data, run workflows, and interact with the platform's Python SDK for complex genomic analyses.

Core Features & Use Cases

App Development: Build and deploy apps/applets on DNAnexus for genomic analysis.
Data Management: Upload/download and organize data objects within DNAnexus.
Job Execution: Run analyses, monitor jobs, and create workflows.
SDK Interaction: Programmatic access to DNAnexus through the dxpy Python SDK.
Use Case: A scientist wants to analyze a large genomic dataset stored on DNAnexus. This Skill allows them to write a Python script using dxpy to download the data, process it, and visualize the results without leaving the DNAnexus platform.

Quick Start

To upload a new file, run the following command:

dxpy.upload_local_file("my_data.txt", project="my_project", folder="/my_folder")

Frequently Asked Questions about dnanexus-integration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I manage and upload genomic data to DNAnexus using Python?▼

You can manage and upload genomic data to DNAnexus using the dxpy Python SDK. For example, the dxpy.upload_local_file function allows you to programmatically upload local files and organize data objects within your specified DNAnexus projects and folders.

What is required to build and deploy apps on the DNAnexus platform?▼

Building and deploying apps on DNAnexus requires the dxpy Python SDK and knowledge of Python programming. This integration provides the necessary tools to develop applets, manage genomic data objects, and execute complex analysis workflows directly on the platform.

Can I execute and monitor genomics workflows programmatically with dxpy?▼

Yes, you can execute and monitor genomics workflows programmatically using the dxpy SDK. The integration provides tools to run analyses, create multi-step workflows, and track job execution statuses for large genomic datasets stored on the DNAnexus cloud platform.

Does DNAnexus integration support processing large genomic datasets without leaving the platform?▼

Yes, DNAnexus integration supports processing large genomic datasets entirely on the platform. You can write Python scripts using dxpy to download data, process it, and visualize results, streamlining complex genomic analyses without needing external infrastructure.

What are the limitations of using the dxpy SDK for genomics workflow management?▼

The dxpy SDK requires prior knowledge of the DNAnexus platform and Python programming to manage genomics workflows effectively. It is specifically targeted at researchers and developers already working within the DNAnexus cloud environment for genomic data analysis.