Can this skill help me build custom DNAnexus applets?

Yes, it provides detailed guidance on using dx-app-wizard, writing Python entry points, and configuring the dxapp.json metadata for platform deployment.

Can I use this with the dxpy Python library?

Absolutely. It contains extensive references and code patterns for the dxpy SDK to automate platform interactions, resource discovery, and API calls programmatically.

How does it handle complex bioinformatics pipelines?

The skill covers job orchestration and workflow creation, allowing you to chain multiple analysis steps, use output references, and manage subjob dependencies.

Does it support large file uploads like FASTQ or BAM?

Yes, it includes standard patterns for managing data objects, uploading local files, and organizing results systematically within DNAnexus projects.

DNAnexus Integration

Name: DNAnexus Integration
Author: Activer007

byActiver007

Data Science & ML

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

About

This skill provides comprehensive support for the DNAnexus cloud genomics platform, enabling developers to build, deploy, and manage bioinformatics apps and workflows. It streamlines the creation of platform-native applets, simplifies data operations like uploading and searching sequencing files (FASTQ, BAM, VCF), and provides deep integration with the dxpy Python SDK for programmatic job execution. Whether you are automating large-scale genomic analyses, managing project resources, or configuring containerized environments, this skill offers the domain-specific patterns and best practices needed to navigate the DNAnexus ecosystem efficiently.

Key Features

Comprehensive data management for uploading, searching, and organizing genomic data objects
Deep Python SDK (dxpy) support for programmatic platform interaction and automation
End-to-end app and applet development including dx-app-wizard and deployment patterns
Job execution and workflow orchestration for parallel processing and multi-step pipelines
Configuration management for dxapp.json specifications, Docker integration, and resource scaling
0 GitHub stars

Use Cases

Managing and organizing large-scale sequencing datasets with metadata across cloud projects
Building and deploying automated bioinformatics pipelines for variant calling and sequence alignment
Orchestrating complex, multi-step genomic analysis workflows with automated error handling

About

Key Features

Comprehensive data management for uploading, searching, and organizing genomic data objects
Deep Python SDK (dxpy) support for programmatic platform interaction and automation
End-to-end app and applet development including dx-app-wizard and deployment patterns
Job execution and workflow orchestration for parallel processing and multi-step pipelines
Configuration management for dxapp.json specifications, Docker integration, and resource scaling
0 GitHub stars

Use Cases

Managing and organizing large-scale sequencing datasets with metadata across cloud projects
Building and deploying automated bioinformatics pipelines for variant calling and sequence alignment
Orchestrating complex, multi-step genomic analysis workflows with automated error handling