Does this skill support GPU acceleration?

Yes, it provides pre-configured task decorators for GPU-intensive workloads, including support for V100 and A100 GPU types for tasks like AlphaFold.

How do I manage cloud storage with this skill?

You can use LatchFile and LatchDir abstractions to handle data transfers between local systems and Latch's cloud storage automatically.

Do I need a Latch account to use this skill?

Yes, you must have a Latch account and be logged in via the Latch CLI to register workflows and access the Registry system.

Can I use this for Nextflow or Snakemake?

Yes, the Latch SDK supports integrating and deploying existing Nextflow and Snakemake pipelines to its serverless infrastructure.

LatchBio is a cloud platform for building and deploying bioinformatics workflows as serverless pipelines using a Python-based SDK built on Flyte.

LatchBio Integration

Name: LatchBio Integration
Author: Activer007

byActiver007

Ciencia de Datos y ML

Builds and deploys serverless bioinformatics pipelines using the Latch SDK and cloud infrastructure.

Acerca de

LatchBio Integration empowers researchers and developers to create production-grade bioinformatics workflows directly within Claude Code. By leveraging the Latch SDK, users can define serverless pipelines with Python decorators, manage large-scale genomic data through cloud abstractions like LatchFile and LatchDir, and configure specialized compute resources including high-performance GPUs. This skill simplifies the end-to-end process of workflow registration, data organization in the Latch Registry, and the utilization of pre-built verified pipelines for tasks like RNA-seq and protein structure prediction.

Características Principales

Serverless workflow deployment with @workflow and @task decorators
0 GitHub stars
Cloud data management using LatchFile and LatchDir abstractions
Integration with Latch Registry for structured genomic data organization
Automated resource configuration for CPU, memory, and multi-GPU tasks
Support for Nextflow, Snakemake, and native Python pipeline conversion

Casos de Uso

Managing and tracking large sequencing datasets using a structured data registry
Running production-ready verified workflows like AlphaFold or DESeq2
Converting local bioinformatics scripts into scalable serverless cloud pipelines

Acerca de

Características Principales

Serverless workflow deployment with @workflow and @task decorators
0 GitHub stars
Cloud data management using LatchFile and LatchDir abstractions
Integration with Latch Registry for structured genomic data organization
Automated resource configuration for CPU, memory, and multi-GPU tasks
Support for Nextflow, Snakemake, and native Python pipeline conversion

Casos de Uso

Managing and tracking large sequencing datasets using a structured data registry
Running production-ready verified workflows like AlphaFold or DESeq2
Converting local bioinformatics scripts into scalable serverless cloud pipelines