dnanexus-integration

DNAnexus Integration - Cloud Genomics Platform and Bioinformatics Analysis Tools

Skill Overview

DNAnexus Integration is an AI skill for cloud-based genomics analysis and bioinformatics workflow development. It helps users build apps on the DNAnexus cloud platform, manage data, run analyses, and automate operations using the dxpy Python SDK.

Applicable Scenarios

1. Genomic Data Analysis and Workflow Development

When you need to process sequencing data in the cloud (FASTQ, BAM, VCF, etc.), build bioinformatics analysis workflows, or develop custom genomics applications, this skill provides full DNAnexus platform support covering the entire process from data upload to result output.

2. Large-scale Data Management and Batch Processing

When you need to manage large numbers of sequencing samples, organize multi-project data, or process multiple analysis tasks in parallel, this skill helps you use DNAnexus’s data object system and job execution features to achieve efficient cloud-based batch processing.

3. Python Automation Script Development

When you need to write automation scripts to manage DNAnexus projects, perform bulk file operations, monitor job status, or integrate DNAnexus into existing workflows, this skill provides full dxpy SDK references and code patterns.

Core Features

1. App Development and Deployment

Provides the complete development workflow for DNAnexus apps and applets, including generating a project skeleton with dx-app-wizard, writing Python/Bash entry points, configuring dxapp.json, and deploying to the platform using dx build. Supports Docker integration, dependency management, and instance type configuration.

2. Data Operations and Management

Covers all data operations on the DNAnexus platform, including file upload/download, record creation and management, data object search, project folder organization, and cross-project data cloning. Supports adding metadata and tags to facilitate data discovery and organization.

3. Job Execution and Workflow Orchestration

Provides complete guidance for running analyses on DNAnexus, monitoring job status, creating child jobs for parallel processing, and building multi-step workflows. Supports job chaining and output referencing, suitable for complex genomics analysis pipelines.

4. dxpy Python SDK

A complete dxpy library reference, including data object handlers such as DXFile, DXRecord, DXApplet, advanced utility functions, and direct API call methods. Provides common code patterns and error handling examples.

5. Configuration and Dependency Management

Detailed dxapp.json specification, including input/output definitions, run specification configuration, system package installation, custom resource packaging, Docker integration, as well as instance types and timeout settings.

Frequently Asked Questions

What is DNAnexus? What do I need to use it?

DNAnexus is a cloud-based biomedical data analysis and genomics platform. To use this skill you need a valid DNAnexus account. The platform supports developing executables (apps/applets), managing data objects, running analysis workflows, and provides the dxpy Python SDK for programmatic access. Common uses include sequence alignment, variant calling, quality control, and format conversion in bioinformatics workflows.

What file formats does DNAnexus support?

As a general data platform, DNAnexus supports all file formats. In genomics, common formats include: FASTQ (sequencing reads), BAM/CRAM (alignment results), VCF (variant calls), BED (genomic intervals), GFF/GTF (gene annotations). This skill provides best practices for handling these formats and common tool integration examples.

How do I get started developing on DNAnexus?

First install dxpy: uv pip install dxpy. Then use dx login to authenticate. You can use dx-app-wizard to quickly generate an app skeleton, write a Python or Bash entry point, configure the dxapp.json file, and finally deploy with dx build. This skill contains complete development reference documentation and code examples covering all scenarios from beginner to advanced.