dnanexus-integration
DNAnexus cloud genomics platform.
Skill by foryourhealth111-pixel
Chalk Labs
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/dnanexus-integration
What's inside
- Skill name
dnanexus-integration- Description
- DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.
- License
- Apache-2.0
- Instructions
- 373 lines in SKILL.md · view on GitHub
Files (6)
- SKILL.md
- app-development.md · references/
- configuration.md · references/
- data-operations.md · references/
- job-execution.md · references/
- python-sdk.md · references/
SKILL.md (first lines)
# DNAnexus Integration ## Overview DNAnexus is a cloud platform for biomedical data analysis and genomics. Build and deploy apps/applets, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution. ## When to Use This Skill This skill should be used when: - Creating, building, or modifying DNAnexus apps/applets - Uploading, downloading, searching, or organizing files and records - Running analyses, monitoring jobs, creating workflows - Writing scripts using dxpy to interact with the platform - Setting up dxapp.json, managing dependencies, using Docker - Processing FASTQ, BAM, VCF, or other bioinformatics files - Managing projects, permissions, or platform resources ## Core Capabilities The skill is organized into five main areas, each with detailed reference documentation: ### 1. App Development **Purpose**: Create executable programs (apps/applets) that run on the DNAnexus platform. **Key Operations**: - Generate app skeleton with `dx-app-wizard` - Write Python or Bash apps with proper entry points - Handle input/output data objects - Deploy with `dx build` or `dx build --app` - Test apps on the platform **Common Use Cases**: - Bioinformatics pipelines (alignment, variant calling) - Data processing workflows - Quality control and filtering - Format conversion tools **Reference**: See `references/app-development.md` for: - Complete app structure and patterns - Python entry point decorators - Input/output handling with dxpy - Development best practices - Common issues and solutions ### 2. Data Operations **Purpose**: Manage files, records, and other data objects on the platform. **Key Operations**: - Upload/download files with `dxpy.upload_local_file()` and `dxpy.download_dxfile()` - Create and manage records with metadata - Search for data objects by name, properties, or type - Clone data between projects - Manage project folders and permissions **Common Use Cases**: - Uploading sequencing data (FASTQ files) - Organizing analysis results - Searching for specific samples or experiments - Backing up data across projects - Managing reference genomes and annotations **Reference**: See `references/data-operations.md` for: - Complete file and record operations - Data object lifecycle (open/closed states) - Search and discovery patterns - Project management - Batch operations ### 3. Job Execution **Purpose**: Run analyses, monitor execution, and orchestrate workflows. **Key Operations**: - Launch jobs with `applet.run()` or `app.run()` - Monitor job status and logs - Create subjobs for parallel processing - Build and run multi-step workflows - Chain jobs with output references **Common Use Cases**: - Running genomics analyses on sequencing data - Parallel processing of multiple samples - Multi-step analysis pipelines - Monitoring long-running computations - Debugging failed jobs **Reference**: See `references/job-execution.md` for: - Complete job lifecycle and states - Workflow creation and orchestration - Parallel execution patterns - Job monitoring and debugging - Resource management ### 4. Python SDK (dxpy) **Purpose**: Programmatic access to DNAnexus platform through Python. **Key Operations**: - Work with data object handlers (DXFile, DXRecord, DXApplet, etc.) - Use high-level functions for common tasks - Make direct API calls for advanced operations - Create links and references between objects - Search and discover platform resources **Common Use Cases**: - Automation scripts for data management - Custom analysis pipelines - Batch processing workflows - Integration with external tools - Data migration and organization **Reference**: See `references/python-sdk.md` for: - Complete dxpy class reference - High-level utility functions - API method documentation - Error handling patterns - Common code patterns
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Signals
- Stars
- 3,764
- Forks
- 341
- Open issues
- 36
- Last commit (this folder)
- Feb 26, 2026 (8 months ago)
- Last release
- Oct 18, 2026 (14 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Website
- agent-skills-hub.github.io/
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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dnanexus-integration skill. Agent Mart. https://agentmart.dev/skills/foryourhealth111-pixel-dnanexus-integration (last updated 2026-10-24)