How does this help with workflow orchestration?

It provides code patterns for launching jobs, monitoring execution status, and chaining outputs from one analysis step into the next.

Does it support the dxpy Python SDK?

Absolutely, it includes detailed references for the dxpy library, data object handlers, and common automation patterns for platform interaction.

How does this skill handle genomics data formats?

The skill provides patterns for managing common bioinformatics files like FASTQ, BAM, and VCF, including uploading, downloading, and metadata management via dxpy.

What is the DNAnexus Integration for Claude Code?

It is a specialized skill that allows Claude to help you write code, manage data, and deploy applications on the DNAnexus cloud genomics platform using best practices.

Can I use this skill for building DNAnexus apps?

Yes, it includes comprehensive guidance for using dx-app-wizard, writing Python/Bash entry points, and configuring dxapp.json files for deployment.

DNAnexus Integration

Name: DNAnexus Integration
Author: Microck

byMicrock

•

Ciencia de Datos y ML

Facilitates the development and management of genomics pipelines on the DNAnexus cloud platform using the dxpy Python SDK and CLI.

Acerca de

The DNAnexus Integration skill empowers developers and bioinformaticians to seamlessly interact with the DNAnexus genomics cloud platform. It provides specialized knowledge for building and deploying apps, managing complex data objects like FASTQ and VCF files, orchestrating large-scale workflows, and utilizing the dxpy SDK for automation. Whether you are automating quality control or building a multi-step variant calling pipeline, this skill streamlines the transition from local code to production-scale cloud execution with detailed guidance on configuration and dependency management.

Características Principales

81 GitHub stars
End-to-end app development and deployment workflows
Comprehensive dxpy Python SDK integration and code patterns
Configuration management for dxapp.json and Docker dependencies
Advanced data management for large-scale genomics files
Automated job execution and multi-step workflow orchestration

Casos de Uso

Chaining multiple analysis steps into scalable genomics pipelines
Automating the upload and organization of sequencing data
Developing and deploying custom bioinformatics apps and applets

Acerca de

Características Principales

81 GitHub stars
End-to-end app development and deployment workflows
Comprehensive dxpy Python SDK integration and code patterns
Configuration management for dxapp.json and Docker dependencies
Advanced data management for large-scale genomics files
Automated job execution and multi-step workflow orchestration

Casos de Uso

Chaining multiple analysis steps into scalable genomics pipelines
Automating the upload and organization of sequencing data
Developing and deploying custom bioinformatics apps and applets