Does this skill support the dxpy Python SDK?

Yes, it provides comprehensive code patterns and guidance for using the dxpy library for automated data operations and job management.

How does this skill assist with app configuration?

It provides detailed references for creating dxapp.json files, managing software dependencies, integrating Docker, and selecting instance types.

Can I automate batch processing with this skill?

Yes, it includes patterns for finding data objects and launching parallel jobs to process multiple samples simultaneously.

What is the primary purpose of the DNAnexus Integration skill?

It is designed to help developers build, deploy, and manage genomics analysis applications and data pipelines on the DNAnexus cloud platform.

Can I use this skill to process sequencing files?

Absolutely. It contains specific patterns for handling common bioinformatics file formats such as FASTQ, BAM, and VCF within the DNAnexus environment.

DNAnexus Integration

Name: DNAnexus Integration
Author: Microck

byMicrock

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数据科学与机器学习

Develops genomics pipelines and manages cloud-based biomedical data using the DNAnexus platform and dxpy Python SDK.

关于

The DNAnexus Integration skill provides specialized guidance for bioinformaticians and developers working on the DNAnexus cloud platform. It facilitates the entire lifecycle of genomic data analysis, from building and deploying custom apps and applets to managing large-scale data objects like FASTQ, BAM, and VCF files. By leveraging the dxpy Python SDK, users can automate job execution, orchestrate complex multi-step workflows, and configure environment dependencies via dxapp.json, ensuring efficient and reproducible bioinformatics research at scale.

主要功能

Scalable job execution and parallel workflow orchestration
89 GitHub stars
Advanced integration with the dxpy Python SDK and DNAnexus API
Full-lifecycle app and applet development for the DNAnexus platform
Programmatic data management including uploads, downloads, and metadata tagging
Bioinformatics-specific support for FASTQ, BAM, and VCF file processing

使用场景

Managing large-scale genomic datasets across collaborative research projects
Automating the upload and quality control of high-throughput sequencing data
Building and deploying production-grade bioinformatics pipelines as cloud applets

关于

主要功能

Scalable job execution and parallel workflow orchestration
89 GitHub stars
Advanced integration with the dxpy Python SDK and DNAnexus API
Full-lifecycle app and applet development for the DNAnexus platform
Programmatic data management including uploads, downloads, and metadata tagging
Bioinformatics-specific support for FASTQ, BAM, and VCF file processing

使用场景

Managing large-scale genomic datasets across collaborative research projects
Automating the upload and quality control of high-throughput sequencing data
Building and deploying production-grade bioinformatics pipelines as cloud applets