latchbio-integration
Build bioinformatics workflows on Latch
也可從以下取得: K-Dense-AI
Building bioinformatics pipelines requires learning platform-specific tools and cloud infrastructure. This skill provides step-by-step guidance for creating serverless workflows using the Latch SDK with decorators, data abstractions, and verified bioinformatics tools.
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正在使用「latchbio-integration」。 Create a Latch workflow for RNA-seq analysis with quality control and alignment
預期結果:
- Define @small_task for quality control (FastQC)
- Define @large_task for alignment (STAR/HISAT2)
- Define @small_task for quantification (featureCounts)
- Create @workflow combining all tasks with LatchFile inputs
- Register workflow with latch register command
正在使用「latchbio-integration」。 Set up GPU resources for protein folding with AlphaFold
預期結果:
- Use @large_gpu_task decorator with V100 or A100 GPU type
- Configure memory allocation based on protein sequence length
- Set appropriate timeout for large protein structure prediction
- Configure output directory with LatchDir for results
正在使用「latchbio-integration」。 Organize my sequencing samples in Latch Registry
預期結果:
- Create a Table with columns for sample_id, condition, and file references
- Use Record class to add samples with metadata
- Link related records for sample relationships
- Query samples using filter criteria in workflows
安全審計
安全Pure documentation skill containing only markdown reference guides. No executable code detected - only code examples in markdown code blocks. All static findings are false positives from scanner misinterpreting documentation examples as executable commands.
風險因素
⚙️ 外部命令 (201)
⚡ 包含腳本 (1)
品質評分
你能建構什麼
Deploy RNA-seq analysis pipelines
Build reproducible RNA-seq pipelines with quality control, alignment, and quantification using verified workflows
Run protein structure prediction
Execute AlphaFold and ColabFold predictions on GPU resources with automatic result organization
Integrate existing pipelines
Port existing Nextflow or Snakemake workflows to cloud with minimal code changes
試試這些提示
Create a Latch workflow for processing FASTQ files with @small_task and @workflow decorators
Configure GPU resources for protein structure prediction using @large_gpu_task or custom_task with A100 GPU
Import my existing Nextflow pipeline to Latch using latch register --nextflow command
Run bulk RNA-seq analysis using the latch.verified.bulk_rnaseq workflow with sample metadata
最佳實務
- Use type annotations for all workflow parameters to enable automatic UI generation
- Start with standard task decorators (@small_task, @large_task) and scale resources only when profiling shows need
- Break complex workflows into modular tasks for better debugging and parallel execution
避免
- Using @large_gpu_task for tasks that do not require GPU acceleration
- Skipping type annotations which disables automatic UI generation
- Over-allocating CPU and memory without profiling actual requirements