service-latchbio-integration

Name: service-latchbio-integration
Availability: InStock
Author: biomaps-infra

Develop and deploy serverless bioinformatics workflows using the Latch SDK.

Updated Mar 13, 2026

Search Tags:#workflow #serverless #data management #bioinformatics #pipeline #gpu #latchsdk

Ready to run

npx skills add https://github.com/biomaps-infra/blender-opencode --skill service-latchbio-integration

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: service-latchbio-integration
Source: https://github.com/biomaps-infra/blender-opencode/tree/main/.opencode/skills/service-latchbio-integration
Command: npx skills add https://github.com/biomaps-infra/blender-opencode --skill service-latchbio-integration

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies the creation, deployment, and management of complex bioinformatics workflows, making advanced computational biology accessible and reproducible.

Core Features & Use Cases

Workflow Development: Design serverless pipelines using Python decorators (@workflow, @task).
Data Management: Utilize cloud-native storage (LatchFile, LatchDir) and a structured Registry for data organization.
Resource Configuration: Easily specify CPU, memory, and GPU requirements for tasks.
Use Case: A researcher needs to analyze genomic data. They can use this Skill to build a pipeline that takes raw sequencing files, performs alignment, variant calling, and generates reports, all managed and deployed through the Latch platform.

Quick Start

Use the service-latchbio-integration skill to create a new Latch workflow named 'my-rnaseq-pipeline'.

Frequently Asked Questions about service-latchbio-integration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build and deploy serverless bioinformatics workflows using Python?▼

You can build serverless bioinformatics workflows by defining pipelines with Python decorators like @workflow and @task. The Latch SDK handles automated containerization and UI generation, allowing you to deploy pipelines directly to the cloud without managing servers.

How do I manage cloud data and configure GPU resources for genomic pipelines?▼

Manage cloud data using LatchFile and LatchDir objects for storage, and organize data through the Latch Registry. You can configure task resources by specifying CPU, memory, and GPU requirements directly within your Python task definitions.

Can I integrate existing Nextflow or Snakemake pipelines with the Latch SDK?▼

Yes, the Latch SDK supports integration with existing Nextflow and Snakemake pipelines. This allows you to incorporate pre-built workflow components while leveraging Latch for serverless deployment and automated UI generation.

What is the best way to make computational biology pipelines reproducible and accessible?▼

Using Python decorators to define workflows ensures reproducibility through automated containerization. The Latch platform generates a user interface automatically, making complex computational biology pipelines accessible without manual web development.

Do I need to manually configure Docker containers when deploying bioinformatics workflows?▼

No, manual Docker container configuration is not required. The Latch SDK supports automated containerization, automatically building the necessary environments for your bioinformatics tasks when you deploy your workflow.