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dnanexus-integration

Interact with the DNAnexus platform using the Python SDK for data and workflow management.

Updated Mar 10, 2026
Search Tags:#bioinformatics#genomics#pipeline#cloud computing#dxpy#dnanexus
One-click install
npx skills add https://github.com/Yezez9/Research-Agent --skill dnanexus-integration-yezez9
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dnanexus-integration
Source: https://github.com/Yezez9/Research-Agent/tree/main/scientific-skills/dnanexus-integration
Command: npx skills add https://github.com/Yezez9/Research-Agent --skill dnanexus-integration-yezez9

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides comprehensive tools and guidance to build, manage, and execute complex genomics pipelines on the DNAnexus cloud platform, streamlining bioinformatics workflows.

Core Features & Use Cases

  • App Development: Build and deploy custom apps/applets for genomics analysis.
  • Data Management: Upload, download, search, and organize large-scale genomics datasets.
  • Pipeline Execution: Run analyses, monitor jobs, and orchestrate multi-step workflows.
  • Python SDK (dxpy): Programmatically interact with the DNAnexus platform for automation.
  • Use Case: A researcher needs to process raw FASTQ sequencing files through an alignment and variant calling pipeline. This Skill enables them to build the necessary applets, upload their data, run the pipeline, and manage the resulting BAM and VCF files efficiently.

Quick Start

Use the dnanexus-integration skill to upload the local file 'sample_data.fastq' to your DNAnexus project 'project-1234'.

Frequently Asked Questions about dnanexus-integration

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

FAQPage Schema
How do I build and deploy a custom bioinformatics app on the DNAnexus platform?▼

To build a custom DNAnexus app, you define the configuration in dxapp.json and use the Python SDK dxpy to package and deploy your genomics analysis applet. This enables programmatic execution of complex bioinformatics workflows.

Can I automate uploading and downloading large-scale genomics datasets using Python?▼

Yes, you can automate genomics data management using the dxpy Python SDK to programmatically upload, download, search, and organize large-scale sequencing datasets within your DNAnexus projects.

What is the best way to execute multi-step workflows for variant calling pipelines in the cloud?▼

The best way to execute multi-step workflows for variant calling is using DNAnexus to orchestrate job execution, monitor analysis progress, and manage resulting sequencing files efficiently in the cloud.

Does this DNAnexus integration support processing raw FASTQ files through to VCF generation?▼

Yes, DNAnexus integration supports processing raw FASTQ sequencing files through alignment and variant calling pipelines, allowing you to manage resulting BAM and VCF files efficiently.

How does dxpy handle reproducible scientific computing for large-scale data analysis?▼

The dxpy Python SDK handles reproducible scientific computing by enabling programmatic interaction with DNAnexus, ensuring consistent execution and management of complex bioinformatics workflows for large-scale genomic data.

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