Nextflow

@nextflow.io

The leading open source orchestrator for containerized, data-intensive pipelines on any infrastructure at any scale. From @seqera.io

Nextflow is the industry standard for reproducible, scalable analysis, now used by all of the top 20 pharma companies.

Welcome to the Program!🎉 We're absolutely delighted to be welcoming 43 new Nextflow Ambassadors to the Program who will help foster collaboration, organize events, and support fellow community members across the global Nextflow ecosystem.🌎

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✨Seqera Co-Scientist is the collaborative agent that understands scientific context and executes with intelligence, helping teams set up infrastructure, develop @nextflow.io pipelines, and interpret results. 🔐Seqera Co-Scientist is an agent that takes action, but with guardrails.

A little-known feature of Nextflow is that it can support iterative processes - feeding process outputs back as inputs until a threshold is met. This is especially useful for ML training, molecular dynamics simulations, and other looped workflows. 📚 Find out more: hubs.la/Q04prlGh0

Running Until: Iterative Loops in Nextflow | Seqera

Nextflow can express iterative loops with a topic channel and an until check. Here's how to make a process feed on its own output, no recursion needed.

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In 2025, we started seeing meaningful adoption of AI and LLMs. Agents can propose more experiments, more analyses, more iterations To do this, agents need to run reproducibly on real data & compute. Nextflow is what makes this possible, bringing control & traceability to the velocity of AI science

Nextflow log files are great for debugging, but digging through 1000s of debug lines to find an error can be difficult Introducing new log viewers in the CLI and VS Code extension, with syntax highlighting and log-level filtering to drill down to a few lines of warnings and errors hubs.la/Q04m8s110

New Nextflow Log Viewers: CLI and VS Code Extension

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Your Infrastructure, Your Pipelines, Your Results. Seqera Co-Scientist is your intelligent collaborator for scientific discovery, from generating @nextflow.io pipelines to autonomously executing at scale. What makes this possible is context.