microck/latchbio-integration
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
This is a copy. The original lives at comeonoliver/skillshub-latchbio-integration.
npx skills add https://github.com/Microck/ordinary-claude-skills --skill latchbio-integrationLatch 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.
The Latch platform provides four main areas of functionality:
# 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:
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)
This skill should be used when encountering any of the following scenarios:
Workflow Development:
@workflow, @task decoratorsData Management:
latch:/// pathsResource Configuration:
Verified Workflows:
latch.verified moduleThis skill includes comprehensive reference documentation organized by capability:
Read this for:
Key topics:
latch init and latch register commands@workflow and @task decoratorsRead this for:
Key topics:
latch:/// path formatRead this for:
Key topics:
@small_task, @large_task, @small_gpu_task, @large_gpu_task@custom_task with precise specificationsRead this for:
Key topics:
latch.verified module importsfrom 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_output
@small_task
def quantification(bam: LatchFile) -> LatchFile:
"""featureCounts"""
return counts
@workflow
def rnaseq_pipeline(
input_fastq: LatchFile,
genome: str,
output_dir: LatchDir
) -> LatchFile:
"""RNA-seq analysis pipeline"""
qc = quality_control(fastq=input_fastq)
aligned = alignment(fastq=qc, genome=genome)
return quantification(bam=aligned)
from latch import workflow, small_task, large_gpu_task
from latch.types import LatchFile
@small_task
def preprocess(input_file: LatchFile) -> LatchFile:
"""Prepare data"""
return processed
@large_gpu_task
def gpu_computation(data: LatchFile) -> LatchFile:
"""GPU-accelerated analysis"""
return results
@workflow
def gpu_pipeline(input_file: LatchFile) -> LatchFile:
"""Pipeline with GPU tasks"""
preprocessed = preprocess(input_file=input_file)
return gpu_computation(data=preprocessed)
from latch import workflow, small_task
from latch.registry.table import Table
from latch.registry.record import Record
from latch.types import LatchFile
@small_task
def process_and_track(sample_id: str, table_id: str) -> str:
"""Process sample and update Registry"""
# Get sample from registry
table = Table.get(table_id=table_id)
records = Record.list(table_id=table_id, filter={"sample_id": sample_id})
sample = records[0]
# Process
input_file = sample.values["fastq_file"]
output = process(input_file)
# Update registry
sample.update(values={"status": "completed", "result": output})
return "Success"
@workflow
def registry_workflow(sample_id: str, table_id: str):
"""Workflow integrated with Registry"""
return process_and_track(sample_id=sample_id, table_id=table_id)
10. Right-size resources (don't over-allocate)
11. Use GPU only when algorithms support it
12. Monitor execution metrics and optimize
13. Design for parallel execution when possible
14. Test locally with Docker before registration
15. Use version control for workflow code
16. Document resource requirements
17. Profile workflows to determine actual needs
Registration Failures:
latch login--verbose flag for detailed logsResource Problems:
Data Access:
latch:/// path formatType Errors:
For issues or questions:
Take microck/latchbio-integration from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip, uv.
Without those the skill loads but fails at the first command.