You can install nf-core/tools from bioconda.

First, install conda and configure the channels to use bioconda (see the bioconda documentation). Then, just run the conda installation command:

conda install nf-core

Alternatively, you can create a new environment with both nf-core/tools and nextflow:

conda create --name nf-core python=3.12 nf-core nextflow
conda activate nf-core

Python Package Index

nf-core/tools can also be installed from PyPI using pip as follows:

pip install nf-core

Docker image

There is a docker image that you can use to run nf-core/tools that has all of the requirements packaged (including Nextflow) and so should work out of the box. It is called nfcore/tools (NB: no hyphen!)

You can use this container on the command line as follows:

docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) nfcore/tools
  • -i and -t are needed for the interactive cli prompts to work (this tells Docker to use a pseudo-tty with stdin attached)
  • The -v argument tells Docker to bind your current working directory (pwd) to the same path inside the container, so that files created there will be saved to your local file system outside of the container.
  • -w sets the working directory in the container to this path, so that it’s the same as your working directory outside of the container.
  • -u sets your local user account as the user inside the container, so that any files created have the correct ownership permissions

After the above base command, you can use the regular command line flags that you would use with other types of installation. For example, to launch the viralrecon pipeline:

docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) nfcore/tools launch viralrecon -r 1.1.0

If you use $NXF_SINGULARITY_CACHEDIR for downloads, you’ll also need to make this folder and environment variable available to the continer:

docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) -v $NXF_SINGULARITY_CACHEDIR:$NXF_SINGULARITY_CACHEDIR -e NXF_SINGULARITY_CACHEDIR nfcore/tools launch viralrecon -r 1.1.0

Docker bash alias

The above base command is a bit of a mouthful to type, to say the least. To make it easier to use, we highly recommend adding the following bash alias to your ~/.bashrc file:

alias nf-core="docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) nfcore/tools"

Once applied (you may need to reload your shell) you can just use the nf-core command instead:

nf-core list

Docker versions

You can use docker image tags to specify the version you would like to use. For example, nfcore/tools:dev for the latest development version of the code, or nfcore/tools:1.14 for version 1.14 of tools. If you omit this, it will default to :latest, which should be the latest stable release.

If you need a specific version of Nextflow inside the container, you can build an image yourself. Clone the repo locally and check out whatever version of nf-core/tools that you need. Then build using the --build-arg NXF_VER flag as follows:

docker build -t nfcore/tools:dev . --build-arg NXF_VER=20.04.0

Development version

If you would like the latest development version of tools, the command is:

pip install --upgrade --force-reinstall git+

If you intend to make edits to the code, first make a fork of the repository and then clone it locally. Go to the cloned directory and install with pip (also installs development requirements):

pip install --upgrade -r requirements-dev.txt -e .

Using a specific Python interpreter

If you prefer, you can also run tools with a specific Python interpreter. The command line usage and flags are then exactly the same as if you ran with the nf-core command. Note that the module is nf_core with an underscore, not a hyphen like the console command.

For example:

python -m nf_core --help
python3 -m nf_core list
~/my_env/bin/python -m nf_core create --name mypipeline --description "This is a new skeleton pipeline"

Using with your own Python scripts

The tools functionality is written in such a way that you can import it into your own scripts. For example, if you would like to get a list of all available nf-core pipelines:

import nf_core.list
wfs = nf_core.list.Workflows()
for wf in wfs.remote_workflows:

Please see for the function documentation.

Update tools

It is advisable to keep nf-core/tools updated to the most recent version. The command to update depends on the system used to install it, for example if you have installed it with conda you can use:

conda update nf-core

if you used pip:

pip install --upgrade nf-core

Please refer to the respective documentation for further details to manage packages, as for example conda or pip.

Automatic version check

nf-core/tools automatically checks the web to see if there is a new version of nf-core/tools available. If you would prefer to skip this check, set the environment variable NFCORE_NO_VERSION_CHECK. For example:


Activate shell completions for nf-core/tools

Auto-completion for the nf-core command is available for bash, zsh and fish. To activate it, add the following lines to the respective shell config files.

shellshell config filecommand
bash~/.bashrceval "$(_NF_CORE_COMPLETE=bash_source nf-core)"
zsh~/.zshrceval "$(_NF_CORE_COMPLETE=zsh_source nf-core)"
fish~/.config/fish/completions/nf-core.fisheval (env _NF_CORE_COMPLETE=fish_source nf-core)

After a restart of the shell session you should have auto-completion for the nf-core command and all its sub-commands and options.

[!NOTE] The added line will run the command nf-core (which will also slow down startup time of your shell). You should therefore either have the nf-core/tools installed globally. You can also wrap it inside if type nf-core > /dev/null; then <YOUR EVAL CODE LINE> fi for bash and zsh or if command -v nf-core &> /dev/null eval (env _NF_CORE_COMPLETE=fish_source nf-core) end for fish. You need to then source the config in your environment for the completions to be activated.

[!TIP] If you see the error command not found compdef , be sure that your config file contains the line autoload -Uz compinit && compinit before the eval line.