dnanexus-integration

Name: dnanexus-integration
Availability: InStock
Author: estrella-231

Automate DNAnexus genomics pipelines with dxpy and dxapp.json.

Updated May 24, 2026

Search Tags:#workflow orchestration #dxpy #dnanexus #genomics pipeline #dxapp.json #fastq bam vcf #data upload download

Ready to run

npx skills add https://github.com/Estrella-231/Mathematical_modeling_tongmeng --skill dnanexus-integration-estrella-231

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dnanexus-integration
Source: https://github.com/Estrella-231/Mathematical_modeling_tongmeng/tree/main/.agents/skills/dnanexus-integration
Command: npx skills add https://github.com/Estrella-231/Mathematical_modeling_tongmeng --skill dnanexus-integration-estrella-231

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

DNAnexus integration removes the friction of uploading genomics data, building executable analysis apps, and reliably running jobs/workflows in a cloud genomics environment.

Core Features & Use Cases

App/Applet development: Create deployable executables on DNAnexus using dx-app-wizard and Python entry points.
Data operations for genomics: Upload, download, search, and organize FASTQ/BAM/VCF inputs and outputs as DNAnexus data objects.
Pipeline execution & automation: Run analyses, monitor job state/logs, chain multi-step workflows, and automate via dxpy using job output references.
Configuration & dependencies: Define dxapp.json inputs/outputs and manage system packages, bundled dependencies, and assets (including Docker-based runs).

Quick Start

Upload a FASTQ file and run an applet by having the AI guide you to write dxpy code that uploads the input, launches the applet, waits for completion, and downloads the resulting BAM.

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 run genomics pipelines on DNAnexus using dxpy?▼

You build and run genomics pipelines on DNAnexus by using the dxpy Python SDK to create applets, configure dxapp.json, and chain multi-step analyses. This automates uploading FASTQ inputs, executing jobs, and downloading BAM outputs.

How do I upload and download FASTQ, BAM, and VCF data objects in a DNAnexus workflow?▼

To upload and download FASTQ, BAM, and VCF data objects, use dxpy to perform deterministic data transfers. This manages sequencing data as DNAnexus objects, organizing inputs and outputs by folders and metadata within your genomics pipeline.

What is the best way to configure dxapp.json for a DNAnexus applet?▼

Configuring dxapp.json involves defining your applet's inputs, outputs, and dependencies. You manage system packages and Docker-based assets within this configuration file to ensure deterministic execution of your genomics pipeline.

Can I chain multi-step analyses and monitor job state in a DNAnexus workflow?▼

Yes, you can chain multi-step analyses and monitor job state by leveraging dxpy with job output references. This allows you to automate pipeline execution, track completion logs, and organize results sequentially.

Does DNAnexus integration support Docker-based app execution and bundled dependencies?▼

DNAnexus integration supports Docker-based app execution and bundled dependencies. You define these system packages and assets within your dxapp.json configuration to create deployable executables for cloud genomics development.

Why use dxpy for DNAnexus cloud genomics development instead of manual data handling?▼

Using dxpy for DNAnexus cloud genomics development removes the friction of manual data handling. It automates building executable apps, managing sequencing data objects, and reliably running end-to-end workflows deterministically.