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latchbio-integration

Develop and deploy serverless bioinformatics workflows using the Latch SDK.

Updated Mar 10, 2026
Search Tags:#workflow#serverless#data management#bioinformatics#pipeline#gpu#latch sdk
One-click install
npx skills add https://github.com/felixboehm/biochem-allergy --skill latchbio-integration-felixboehm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: latchbio-integration
Source: https://github.com/felixboehm/biochem-allergy/tree/main/.claude/skills/latchbio-integration
Command: npx skills add https://github.com/felixboehm/biochem-allergy --skill latchbio-integration-felixboehm

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 efficient.

Core Features & Use Cases

  • Workflow Development: Define serverless pipelines using Python decorators (@workflow, @task).
  • Data Management: Seamlessly handle cloud data with LatchFile and LatchDir, and organize experiments using the Latch Registry.
  • Resource Optimization: Configure precise CPU, memory, and GPU requirements for tasks.
  • Use Case: A researcher needs to analyze a large RNA-seq dataset. They can use this Skill to define a pipeline that handles data QC, alignment, and differential expression analysis, all deployable as a serverless function.

Quick Start

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

Frequently Asked Questions about latchbio-integration

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

FAQPage Schema
How do I deploy serverless bioinformatics pipelines?▼

Deploy serverless bioinformatics pipelines by defining workflows with Python decorators like @workflow and @task using the Latch SDK. This approach enables reproducible, scalable, and automated computational biology pipelines without infrastructure management.

Can I run Nextflow and Snakemake pipelines on serverless infrastructure?▼

Nextflow and Snakemake pipelines are supported for serverless deployment alongside Python. The Latch SDK handles the deployment, allowing you to run existing pipeline frameworks without managing servers.

How do I manage cloud data for an RNA-seq pipeline?▼

Manage cloud data for RNA-seq pipelines using LatchFile and LatchDir objects. The Latch Registry also allows you to organize and track experiments seamlessly within your serverless workflows.

Does serverless workflow deployment support GPU configurations?▼

Serverless workflow deployment supports flexible resource configuration including precise CPU, memory, and GPU requirements. You can configure these parameters for individual tasks to optimize computational biology workloads.

What is the best way to build reproducible computational biology pipelines?▼

Build reproducible computational biology pipelines by defining serverless workflows with Python decorators. This method handles data management and resource configuration, ensuring scalable and automated analysis.

How do I configure CPU and memory for specific bioinformatics tasks?▼

Configure CPU and memory for bioinformatics tasks by specifying resource requirements within the task definition. The Latch SDK allows precise allocation of compute resources, including GPU support, for individual pipeline steps.

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