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/latchbio-integration

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

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$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill latchbio-integration --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/latchbio-integration

Context preview

The summary Claude sees to decide when to auto-load this skill.

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

SKILL.md

latchbio-integration.SKILL.md
name: latchbio-integration
description: Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
license: Unknown
metadata:
    skill-author: K-Dense Inc.

LatchBio Integration

Overview

Latch is a Python framework for building and deploying bioinformatics workflows as serverless pipelines. Built on Flyte, create workflows with @workflow/@task decorators, manage cloud data with LatchFile/LatchDir, configure resources, and integrate Nextflow/Snakemake pipelines.

Core Capabilities

The Latch platform provides four main areas of functionality:

1. Workflow Creation and Deployment

  • Define serverless workflows using Python decorators
  • Support for native Python, Nextflow, and Snakemake pipelines
  • Automatic containerization with Docker
  • Auto-generated no-code user interfaces
  • Version control and reproducibility

2. Data Management

  • Cloud storage abstractions (LatchFile, LatchDir)
  • Structured data organization with Registry (Projects → Tables → Records)
  • Type-safe data operations with links and enums
  • Automatic file transfer between local and cloud
  • Glob pattern matching for file selection

3. Resource Configuration

  • Pre-configured task decorators (@small_task, @large_task, @small_gpu_task, @large_gpu_task)
  • Custom resource specifications (CPU, memory, GPU, storage)
  • GPU support (K80, V100, A100)
  • Timeout and storage configuration
  • Cost optimization strategies

4. Verified Workflows

  • Production-ready pre-built pipelines
  • Bulk RNA-seq, DESeq2, pathway analysis
  • AlphaFold and ColabFold for protein structure prediction
  • Single-cell tools (ArchR, scVelo, emptyDropsR)
  • CRISPR analysis, phylogenetics, and more

Quick Start

Installation and Setup

# Install Latch SDK
python3 -m uv pip install latch

# Login to Latch
latch login

# Initialize a new workflow
latch init my-workflow

# Register workflow to platform
latch register my-workflow

**Prerequisites:**

  • Docker installed and running
  • Latch account credentials
  • Python 3.8+

Basic Workflow Example

from latch import workflow, small_task
from latch.types import LatchFile

@small_task
def process_file(input_file: LatchFile) -> LatchFile:
    """Process a single file"""
    # Processing logic
    return output_file

@workflow
def my_workflow(input_file: LatchFile) -> LatchFile:
    """
    My bioinformatics workflow

    Args:
        input_file: Input data file
    """
    return process_file(input_file=input_file)

When to Use This Skill

This skill should be used when encountering any of the following scenarios:

**Workflow Development:**

  • "Create a Latch workflow for RNA-seq analysis"
  • "Deploy my pipeline to Latch"
  • "Convert my Nextflow pipeline to Latch"
  • "Add GPU support to my workflow"
  • Working with `@workflow`, `@task` decorators

**Data Management:**

  • "Organize my sequencing data in Latch Registry"
  • "How do I use LatchFile and LatchDir?"
  • "Set up sample tracking in Latch"
  • Working with `latch:///` paths

**Resource Configuration:**

  • "Configure GPU for AlphaFold on Latch"
  • "My task is running out of memory"
  • "How do I optimize workflow costs?"
  • Working with task decorators

**Verified Workflows:**

  • "Run AlphaFold on Latch"
  • "Use DESeq2 for differential expression"
  • "Available pre-built workflows"
  • Using `latch.verified` module

Detailed Documentation

This skill includes comprehensive reference documentation organized by capability:

references/workflow-creation.md

**Read this for:**

  • Creating and registering workflows
  • Task definition and decorators
  • Supporting Python, Nextflow, Snakemake
  • Launch plans and conditional sections
  • Workflow execution (CLI and programmatic)
  • Multi-step and parallel pipelines
  • Troubleshooting registration issues

**Key topics:**

  • `latch init` and `latch register` commands
  • `@workflow` and `@task` decorators
  • LatchFile and LatchDir basics
  • Type annotations and docstrings
  • Launch plans with preset parameters
  • Conditional UI sections

references/data-management.md

**Read this for:**

  • Cloud storage with LatchFile and LatchDir
  • Registry system (Projects, Tables, Records)
  • Linked records and relationships
  • Enum and typed columns
  • Bulk operations and transactions
  • Integration with workflows
  • Account and workspace management

**Key topics:**

  • `latch:///` path format
  • File transfer and glob patterns
  • Creating and querying Registry tables
  • Column types (string, number, file, link, enum)
  • Record CRUD operations
  • Workflow-Registry integration

references/resource-configuration.md

**Read this for:**

  • Task resource decorators
  • Custom CPU, memory, GPU configuration
  • GPU types (K80, V100, A100)
  • Timeout and storage settings
  • Resource optimization strategies
  • Cost-effective workflow design
  • Monitoring and debugging

**Key topics:**

  • `@small_task`, `@large_task`, `@small_gpu_task`, `@large_gpu_task`
  • `@custom_task` with precise specifications
  • Multi-GPU configuration
  • Resource selection by workload type
  • Platform limits and quotas

references/verified-workflows.md

**Read this for:**

  • Pre-built production workflows
  • Bulk RNA-seq and DESeq2
  • AlphaFold and ColabFold
  • Single-cell analysis (ArchR, scVelo)
  • CRISPR editing analysis
  • Pathway enrichment
  • Integration with custom workflows

**Key topics:**

  • `latch.verified` module imports
  • Available verified workflows
  • Workflow parameters and options
  • Combining verified and custom steps
  • Version management

Common Workflow Patterns

Complete RNA-seq Pipeline

from latch import workflow, small_task, large_task
from latch.types import LatchFile, LatchDir

@small_task
def quality_control(fastq: LatchFile) -> LatchFile:
    """Run FastQC"""
    return qc_output

@large_task
def alignment(fastq: LatchFile, genome: str) -> LatchFile:
    """STAR alignment"""
    return bam_outp
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