latchbio-integration

Deploy serverless bioinformatics pipelines on Latch by implementing Python @workflow and @task decorators. This method integrates containerization for reproducibility and deploys Flyte-backed workflows to the cloud.

Manage cloud data inputs using LatchFile and LatchDir by referencing latch:/// paths. This approach handles automatic file transfer and supports glob-based file selection to organize and retrieve data within your workflow.

Yes, you can configure CPU and GPU resources for individual tasks in a Latch workflow. Apply resource sizing directly within the task decorators to match the compute requirements of specific pipeline components.

The best way to run standard analyses like RNA-seq, AlphaFold, or single-cell tools on Latch is by leveraging production-ready verified workflows. These pre-existing pipelines ensure consistent inputs and outputs for common bioinformatics tasks.

Yes, Latch supports typed file abstractions for bioinformatics pipeline development. The platform uses LatchFile and LatchDir objects to ensure consistent cloud data management and automatic file transfer for your workflows.

Move bioinformatics pipeline development to serverless workflows to achieve consistent inputs and outputs alongside cloud-managed files. This transition eliminates local compute limitations and standardizes data processing through registry-driven organization.