Does this skill help with managing cloud costs on DNAnexus?

Yes, it includes best practices for resource management, such as selecting appropriate instance types and optimizing data storage through systematic organization and cleanup.

How does it handle large-scale data processing?

The skill provides patterns for batch processing, subjob creation for parallel execution, and efficient data handling using the dxpy library to ensure scalability across thousands of samples.

Can I use this for Docker-based app development?

Absolutely. The skill covers patterns for integrating Docker containers, managing system dependencies via execDepends, and building portable bioinformatics tools.

What is the primary benefit of using this skill with Claude?

It provides domain-specific knowledge for the DNAnexus platform, helping you write accurate dxpy code, configure app metadata correctly, and implement complex genomics workflows without constant manual reference checks.

DNAnexus Integration

Name: DNAnexus Integration
Author: Activer007

byActiver007

클라우드 인프라

Streamlines bioinformatics pipeline development and data management on the DNAnexus cloud genomics platform.

소개

This skill provides specialized support for the DNAnexus platform, a cloud-based environment for biomedical data analysis and genomics. It enables developers to build and deploy apps, manage large-scale genomic data objects (like FASTQ, BAM, and VCF files), and orchestrate complex workflows using the dxpy Python SDK. By offering deep integration with platform-specific patterns—from dxapp.json configuration and dependency management to job monitoring and subjob parallelization—it helps bioinformaticians accelerate research and maintain robust production-grade analysis pipelines.

주요 기능

Comprehensive data operations for managing, searching, and organizing genomic files
Dependency and resource management using dxapp.json, Docker, and assets
Programmatic platform access via standardized dxpy SDK implementation patterns
0 GitHub stars
End-to-end app and applet development with dx-app-wizard and Python entry points
Advanced job orchestration for parallel processing and multi-step workflow chaining

사용 사례

Building and deploying automated genomic variant calling or sequence alignment pipelines
Batch processing massive sequencing datasets with parallelized cloud compute resources
Developing custom bioinformatics tools with complex system dependencies and containerization

소개

주요 기능

Comprehensive data operations for managing, searching, and organizing genomic files
Dependency and resource management using dxapp.json, Docker, and assets
Programmatic platform access via standardized dxpy SDK implementation patterns
0 GitHub stars
End-to-end app and applet development with dx-app-wizard and Python entry points
Advanced job orchestration for parallel processing and multi-step workflow chaining

사용 사례

Building and deploying automated genomic variant calling or sequence alignment pipelines
Batch processing massive sequencing datasets with parallelized cloud compute resources
Developing custom bioinformatics tools with complex system dependencies and containerization