latchbio-integration

Files (7)

• SKILL.md
• data-management.md · references/
• resource-configuration.md · references/
• verified-workflows.md · references/
• workflow-creation.md · references/
• demo.cpython-313.pyc · scripts/__pycache__/
• demo.py · scripts/

SKILL.md (first lines)

# 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

```bash
# 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

```python
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
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From lamm-mit/scienceclaw, Apache-2.0.

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