Latch Workflows

Run Nextflow® Based Pipelines at Scale

Integrate workflows built with Nextflow® on the platform hundreds of biotechs use to make data analysis faster, cheaper, more accessible, and instantly accelerate their R&D milestones.

Documentation

An optimized platform for workflows built with Nextflow®

Latch addresses infrastructure challenges for workflows built with Nextflow® and facilitates their delivery to scientists.

User-friendly, Type-safe Interfaces

Latch integrates with workflows built with Nextflow®, enabling developers to create user-friendly graphical interfaces accessible to wet lab scientists.

No changes required to existing Nextflow code

Customizable interface via an additional Python file

Bring data from anywhere - AWS, GCP, SRA, BaseSpace, and more.

Downstream analysis tooling

With Latch, scientists can transform raw output files from workflows built with Nextflow® into interactive visualizations, facilitating critical scientific decisions.

Results to Plots

Downstream analyses in Pods

Native visualizations (FastQC, CELLxGENE) for common files

Built for Developers.

Latch offers managed cloud infrastructure for executing, debugging, and analyzing workflows built with Nextflow®.

It uses a customized Nextflow Kubernetes plugin to run processes in containers within Latch’s Kubernetes cluster, which allows developers to use existing Nextflow projects with minimal code alterations.

Intermediate outputs are shared via AWS EFS, and final outputs can be uploaded to Latch Data using a custom plugin.

The Latch Console features a Directed Acyclic Graph (DAG) for monitoring progress, checking logs, and analyzing process costs and runtime. Developers also have real-time access to the container for debugging purposes.

Deploy existing Nextflow workflows with minimal changes

Migrate workflows built with Nextflow® to LatchBio in three simple steps while maintaining full portability.

Nextflow nf-core rna-seq project folder structure with code registration command in LatchBio for efficient workflow deployment.

Boost pipeline throughput and reduce cost via a shared filesystem

Enhance performance of workflows built with Nextflow® by using a shared filesystem for efficient data handling.

Nextflow tasks using a shared filesystem to boost pipeline throughput, showing efficient data handling across different stages.

Optimize workflows with real-time per process cost and runtime reporting

Obtain real-time insights on costs and runtime for each process in workflows built with Nextflow® to optimize efficiency.

Graphical report of Nextflow task CPU usage and runtime over time, providing real-time performance insights for workflow optimization.

Scalable and reliable for large workloads

Manage large-scale workflows built with Nextflow® using LatchBio’s scalable, high-performance infrastructure.

Visualization of a Nextflow workflow DAG showing parallel tasks with runtime in a bioinformatics pipeline, from input to output.

Retry from failed tasks

Quickly modify and relaunch workflows built with Nextflow® from the point of failure without re-entering parameters or restarting the entire workflow.

Nextflow interface showing the ability to relaunch a workflow from a failed task, ensuring recovery without restarting from the beginning.

Designed for reproducibility with GitHub integration

Ensure reproducibility of workflows built with Nextflow® through automatic linking of versions to corresponding GitHub commits.

Version control view showing Nextflow workflow releases linked to GitHub commits for automatic reproducibility and tracking.

How it works

Upload your own

Install Latch & Clone your repositories containing workflows built with Nextflow®

$pip install latch$git clone https://github.com/nf-core/rnaseq$cd rnaseq

Define metadata and workflow graphical interface

$latch generate-metadata nextflow_schema.json --nextflow

Metadata files:

latch_metadata/__init__.py

latch_metadata/parameters.py

Register the workflow to Latch

$latch login$latch register . --nf-script main.nf --nf-execution-profile docker

– and that’s it. You just uploaded the nf-core/rnaseq pipeline to Latch!

Documentation

Or access the nf-core library on Latch

nf-core/rnaseq

nf-core/sarek

nf-core/scrnaseq

nf-core/methylseq

nf-core/mag

nf-core/atacseq

nf-core/nanoseq

nf-core/ampliseqs

nf-core/cutandrun

nf-core/bacass

Each pipeline on Latch has a user-friendly interface, a graphical, error-validated sample sheet component to fill out pipeline inputs, and a directed acyclic graph (DAG) to view process and sample-specific errors.

For Bulk RNA-seq, ATAC-seq, and Methyl-seq, Latch also offers interactive plotting dashboards that directly ingest NF-core outputs and produce publication-ready figures.

Features

Performance Optimization

Easily view and compare results, cost, and performance of different executions

Graphical workflow interface

Easily view and compare results, cost, and performance of different executions

Integration with Latch Registry

Developers can extend their existing Nextflow workflow to read from Latch Registry, a user-friendly, error-validated sample sheet input system.

Debugging

Avoid failed workflows caused by discrepancies between running code locally and in the cloud.

Latch SDK comes with the latch develop command, which drops you into an interactive shell where you can run your code and inspect the environment before registering and executing the entire workflow in the cloud to debug environments and logical issues.

Relaunching from failed tasks

Nextflow's integration uses caching to save intermediate workflow results, allowing for relaunch without full re-execution.

Latch also exposes storage expiration hours as a configurable parameter to users to determine how long the cache will persist after a failure.

Logging

To facilitate debugging, a DAG of processes is generated in the Latch console to enable developers to easily track progress, view logs, and analyze cost and runtime of each process execution.

EFS integration

Intermediate outputs are communicated between processes via AWS EFS and published outputs can be uploaded directly to Latch Data via a custom filesystem plugin. The work directory is automatically cleaned up after workflow completion, saving costs and eliminating the hassle of manually cleaning up resources

Ready-to-use NF-core pipelines

Latch has top 10 ready-to-launch NF-core workflows with user-friendly interfaces, documentation, and GitHub repositories to help you get started.

Sharing of pipelines

There’s no seat limit on Latch. Everyone with a Latch account can create any number of workspaces and add unlimited team members to each workspace. As an Admin, user can also distribute versions of their Nextflow pipelines to multiple workspaces.

Private registries

Latch Secrets allow Nextflow processes on Latch to securely use containers images hosted in users’ private registries (GitLab, AWS ECR, Azure container registry, and more)

Integration with GitHub

Workflows on Latch can be versioned using Git. If the SDK detects that the project directory is a Git repository, it will append the first six digits of the latest commit hash to the workflow version.

Pay-as-you-go. No commitment upfront.

There’s no license fee on Latch. You can add unlimited number of users on the platform, and only pay for compute and storage.

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