Does it support multi-step workflow orchestration?

Yes, it provides patterns for chaining jobs together, creating subjobs for parallel processing, and passing output references between analysis steps.

Can I use this for bioinformatics file management?

Absolutely. It includes specific guidance for handling large files like FASTQ, BAM, and VCF, including upload, download, and metadata tagging operations.

Does this skill support the Python dxpy SDK?

Yes, it provides detailed patterns and documentation for writing Python scripts to interact with DNAnexus objects, handlers, and APIs.

How does it help with app deployment?

It assists in creating dxapp.json configurations, managing system dependencies via Docker or execDepends, and using CLI tools to push apps to the platform.

What is the DNAnexus Integration skill for?

It helps developers build, deploy, and manage genomics applications and data on the DNAnexus cloud platform using Claude's AI assistance.

DNAnexus Genomics Integration

Name: DNAnexus Genomics Integration
Author: Activer007

byActiver007

Cloud Infrastructure

Integrates Claude with the DNAnexus cloud platform to build genomics pipelines, manage biomedical data, and automate workflows using the dxpy SDK.

About

This skill empowers developers and bioinformaticians to interact seamlessly with the DNAnexus platform directly through Claude. It provides specialized support for building and deploying cloud apps, managing massive genomic datasets like FASTQ and BAM files, and orchestrating complex analysis workflows. By leveraging the dxpy Python SDK and platform-specific configurations like dxapp.json, the skill streamlines the entire lifecycle of biomedical data science—from initial data upload and project organization to high-performance job execution and resource management.

Key Features

Dependency management using Docker and dxapp.json specifications
0 GitHub stars
App and applet development with dx-app-wizard and dx build
Comprehensive data management for genomic files and metadata
Automated job execution and multi-step workflow orchestration
Detailed dxpy Python SDK reference and implementation patterns

Use Cases

Building automated bioinformatics pipelines for sequence alignment and variant calling
Scripting batch processing jobs and monitoring cloud execution logs
Managing large-scale genomic data uploads and systematic project organization

About

Key Features

Dependency management using Docker and dxapp.json specifications
0 GitHub stars
App and applet development with dx-app-wizard and dx build
Comprehensive data management for genomic files and metadata
Automated job execution and multi-step workflow orchestration
Detailed dxpy Python SDK reference and implementation patterns

Use Cases

Building automated bioinformatics pipelines for sequence alignment and variant calling
Scripting batch processing jobs and monitoring cloud execution logs
Managing large-scale genomic data uploads and systematic project organization