How does this skill handle large genomic datasets?

It utilizes LatchFile and LatchDir abstractions for cloud storage and the Latch Registry for structured data organization, ensuring type-safe data operations and automatic file transfers.

Does this skill require specific local setup?

Users need the Latch SDK installed via pip, an active Latch account, and Docker running locally to initialize and register workflows.

What are 'Verified Workflows' in this context?

Verified Workflows are production-ready, pre-built pipelines for common tasks like bulk RNA-seq, pathway analysis, and single-cell tools that can be easily imported and run.

What is the primary purpose of the LatchBio integration?

The integration allows users to build, deploy, and manage serverless bioinformatics workflows on the Latch platform using Python, Nextflow, or Snakemake.

Can I use this skill for GPU-intensive tasks like AlphaFold?

Yes, the skill includes patterns for configuring GPU resources (K80, V100, A100) using specialized task decorators to support intensive computational biology models.

LatchBio Bioinformatics Integration

Name: LatchBio Bioinformatics Integration
Author: ricable

byricable

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데이터 과학 및 ML

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

소개

This skill empowers bioinformaticians and developers to architect, deploy, and manage complex genomic pipelines on the Latch platform. It provides specialized implementation patterns for creating Python-based workflows using @workflow and @task decorators, managing massive datasets with LatchFile and LatchDir, and orchestrating high-performance computing resources including multi-GPU configurations for tools like AlphaFold. By bridging the gap between local development and serverless cloud execution, this skill ensures scientific workflows remain reproducible, scalable, and integrated with the Latch Registry for structured data tracking.

주요 기능

Serverless workflow orchestration using Python decorators (@workflow/@task)
Integration with production-ready verified workflows for RNA-seq and CRISPR analysis
1 GitHub stars
Cloud data abstractions with LatchFile, LatchDir, and Latch Registry
Native support for containerizing Nextflow and Snakemake pipelines
Automated resource configuration for high-memory and GPU (A100/V100) tasks

사용 사례

Deploying scalable RNA-seq and differential expression pipelines to the cloud
Organizing large-scale sequencing data and metadata within the Latch Registry system
Running GPU-accelerated protein structure predictions with AlphaFold and ColabFold

소개

주요 기능

Serverless workflow orchestration using Python decorators (@workflow/@task)
Integration with production-ready verified workflows for RNA-seq and CRISPR analysis
1 GitHub stars
Cloud data abstractions with LatchFile, LatchDir, and Latch Registry
Native support for containerizing Nextflow and Snakemake pipelines
Automated resource configuration for high-memory and GPU (A100/V100) tasks

사용 사례

Deploying scalable RNA-seq and differential expression pipelines to the cloud
Organizing large-scale sequencing data and metadata within the Latch Registry system
Running GPU-accelerated protein structure predictions with AlphaFold and ColabFold