/nextflow

name: nextflow
description: Builds, runs, and debugs Nextflow DSL2 pipelines and nf-core workflows. Use for Nextflow, nf-core, .nf files, nextflow.config, processes/channels/operators, samplesheets, nf-test, modules/subworkflows, container and executor configuration, HPC/SLURM or cloud deployment, and failed or resumed pipeline runs.
license: Apache-2.0
compatibility: Requires Bash 3.2+, Java 17-26 and Nextflow. nf-core tools requires Python 3.10+. Containers, scheduler access and network or service credentials depend on the selected workflow.
metadata:
  version: "1.4"
  last-reviewed: "2026-10-01"
  upstream-versions: "Nextflow 26.04.6; nf-core tools 4.1.0; nf-test 0.9.5"
  skill-author: K-Dense Inc.

Nextflow

Overview

Nextflow is a workflow language and runtime for building **reproducible, portable, scalable** data pipelines. It is dominant in bioinformatics but works for any data-heavy computation. nf-core is a community curating production-grade Nextflow pipelines, reusable modules, and the `nf-core` tooling on top of Nextflow.

Key ideas:

• **Dataflow programming**: pipelines are `process` tasks connected by **channels**. Nextflow infers execution order and parallelism from data dependencies — there is no explicit scheduler to write.
• **Write once, run anywhere**: the same pipeline runs locally, on HPC (SLURM, SGE, LSF, PBS), and on cloud (AWS Batch, Google Batch, Azure Batch, Kubernetes) by changing config/profiles, not code.
• **Reproducibility**: pinned software environments and pipeline revisions, immutable inputs/references, recorded parameters and seeds. `-resume` is a computational cache, not scientific validation. Conda is an environment manager; Wave resolves/builds images rather than executing them.
• **DSL2** is the modern, required syntax: modular `process`/`workflow`/`include` definitions.

This skill covers both **running** existing pipelines and **developing** your own (Nextflow language + nf-core conventions, testing with nf-test, configuration, and deployment).

When to Use This Skill

Use this skill when the user wants to:

• Run an nf-core or custom Nextflow pipeline, or debug a failing/resuming run.
• Write or modify `.nf` scripts, `nextflow.config`, profiles, or `nextflow_schema.json`.
• Author or test nf-core-style modules/subworkflows (`main.nf`, `meta.yml`, `tests/`, nf-test).
• Configure executors, containers, or resources; scale to HPC or cloud.
• Implement a scientific workflow in Nextflow or adapt an existing nf-core pipeline.
• Understand processes, channels, operators, `take`/`emit`, `publishDir`, `ext.args`, meta maps.

Setup

This review targets stable **Nextflow 26.04.6**, **nf-core tools 4.1.0**, and **nf-test 0.9.5**. Nextflow needs **Bash 3.2+** and **Java 17–26**; verify `java -version` (a launcher on PATH does not prove a runtime is installed). The strict parser is the default in 26.04. See [release notes](https://github.com/nextflow-io/nextflow/releases/tag/v26.04.6) and the [26.04 migration guide](https://docs.seqera.io/nextflow/migrations/26-04). Stable and edge documentation can differ; do not use a preview feature without its version/flag.

# Install Nextflow (self-installing launcher)
export NXF_VER=26.04.6
curl -fsSL https://get.nextflow.io -o install-nextflow.sh
# Review the installer before executing it.
bash < install-nextflow.sh
mkdir -p "$HOME/.local/bin"
mv nextflow "$HOME/.local/bin/"
export PATH="$HOME/.local/bin:$PATH"
nextflow info                                # verify

# Alternative (illustrative; confirm package availability and Java compatibility)
conda create -n nf -c conda-forge -c bioconda nextflow=26.04.6 nf-core=4.1.0

# nf-core tools (Python) for creating/linting/running nf-core assets
uv tool install "nf-core==4.1.0"
nf-core --version

Pin the engine for reproducibility: `export NXF_VER=26.04.6`; check the selected pipeline release’s engine constraint before upgrading. Use edge only for a required, explicitly tested feature. For air-gapped/HPC, see `references/running-pipelines.md` (offline mode) and `references/configuration.md`.

Two Modes of Work

Decide which path the user is on — it changes everything:

| Goal | Start here | |------|-----------| | **Run** an existing pipeline (nf-core or a `.nf` you were given) | `references/running-pipelines.md` | | **Develop** a new pipeline / module / subworkflow | `references/language.md` + `references/developing.md` | | **Configure / scale** (HPC, cloud, containers, resources) | `references/configuration.md` + `references/containers.md` | | **Test** modules/pipelines | `references/testing.md` |

Quick Start

Run an nf-core pipeline

Use the selected release’s small `test` profile first after checking its resource/download requirements. A passing smoke test verifies that configuration and fixture, not scientific accuracy or full-scale capacity. The following RNA-seq examples are illustrative; no biological pipeline or containers were run in this review.

# 1. Confirm setup works (downloads pipeline + tiny test data)
nextflow run nf-core/rnaseq -r 3.27.0 -profile test,docker --outdir test_results

# 2. Real run: pin a revision (-r), pick a container engine, pass inputs
nextflow run nf-core/rnaseq -r 3.27.0 \
  -profile docker \
  --input samplesheet.csv \
  --fasta reference.fa --gtf annotation.gtf \
  --outdir results \
  -resume

• `-profile` (single dash) selects bundled config profiles; **combine** them comma-separated, e.g. `test,docker`. Choose one execution environment profile (`docker`, `singularity`, or `conda`); a site/executor profile can be combined with it when compatible.
• `--input`, `--genome`, `--outdir` (double dash) are **pipeline** parameters. Many nf-core pipelines take a **samplesheet CSV**; use the selected pipeline release’s input schema.
• `-resume` reuses cached results from the last run. `-r <version>` pins a release for reproducibility.

Use `nf-core pipelines launch <name>` for an