All nf-core pipelines use Nextflow, so this must be present on the system where you launch your analysis. See for the latest installation instructions.

Generally speaking, Nextflow runs on most POSIX systems (Linux, Mac OSX etc) and can typically be installed by running the following commands:

# Make sure that Java v8+ is installed:
java -version

# Install Nextflow
curl -fsSL | bash

# Add Nextflow binary to your user's PATH:
mv nextflow ~/bin/
# OR system-wide installation:
# sudo mv nextflow /usr/local/bin

You can also install Nextflow using Bioconda:

conda install -c bioconda nextflow

We recommend using a personal installation of Nextflow where possible, instead of using a system-wide installation. This makes it easier to update.

Updating nextflow is as simple as running nextflow self-update or conda update nextflow, depending on how it was installed.

Once installed you will probably need to configure Nextflow to run on your system. For instructions, see Nextflow configuration.

Pipeline software

An analysis pipeline chains the execution of multiple tools together. Historically, all tools would have to be manually installed, often a source of great frustration and a key step where reproducibility between analyses is lost. nf-core pipelines utilise the built-in support for software packaging that Nextflow offers: all can work with Docker and Singularity, and most pipelines also have support for Conda.

Pipeline code


This pipeline itself needs no installation - nextflow will automatically fetch it from GitHub if nf-core/<pipeline-name> is specified as the pipeline name.

This method requires an internet connection. If you're running on a system that has no internet connection, please see the Running Offline documentation.


If you would like to make changes to the pipeline, fork the GitHub repository and then clone the files. Once cloned you can run the pipeline with nextflow run <path-to-repo>.

Note that you should only do this if you intend to make significant changes to the pipeline. All configuration options can be changed without editing the pipeline code. Forking the pipeline repositories means that you cannot use stable releases and you will fall behind new updates.

Reference genomes

Some pipelines come with built-in support for iGenomes references. It may be preferable for you to download a local copy of these to your system to avoid fetching the same reference many times. For more information, see Reference genomes.