sudo apt -y upgrade
sudo apt install ubuntu-restricted-extras
sudo apt install -y build-essential libssl-dev libffi-dev python3-dev
sudo apt install git
sudo apt install tree

Download latest miniconda linux installer from website and move to /tmp. /tmp is a good directory to download ephemeral items, like the miniconda bash script, which you won’t need after running it.

You can now verify the data integrity of the installer with cryptographic hash verification through the SHA-256 checksum: sha256sum miniconda.sh

You can now run the script: bash anaconda.sh and say yes to everything

You can now activate the installation by sourcing the ~/.bashrc file: source ~/.bashrc

You can now create a conda environment (to look up available python versions type: conda search python): conda create --name env_scil python=3.7

You can activate your new environment by typing: conda activate env_scil and deactivate by typing: conda deactivate

To remove conda environment deactivate and type: conda remove --name env_scil --all

To list all environments type: conda info --envs

To activate conda env in shell script use command:

source /home/pabaua/miniconda3/etc/profile.d/conda.sh
conda init bash
conda activate env_scil

Install java by running command: sudo apt install default-jre and sudo apt install default-jdk

Download latest nextflow version (not edge version) from Github releases

Make the binary executable on your system by running chmod +x nextflow.

Optionally, move the nextflow file to a directory accessible by your $PATH variable (this is only required to avoid remembering and typing the full path to nextflow each time you need to run it). Example: sudo mv ~/Downloads/nextflow /usr/local/bin

You can temporarily switch to a specific version of Nextflow by prefixing the nextflow command with the NXF_VER environment variable. For example: NXF_VER=20.04.0 nextflow run

Singularity is used to package scientific software and deploy that package to different clusters having the same environment.

Install singularity with the debian package on the Github repository releases then run download folder: sudo dpkg -i singularity-ce_3.10.0-jammy_amd64.deb

Enter command line: singularity remote login

Then enter access token from: https://cloud.sylabs.io/dashboard

This will allow to build singularity image without sudo using command

singularity build --remote .img .def

Create directories in HOME: mkdir dev_tpil dev_scil

Create directories in Documents: mkdir tpil

Create directories in tpil: mkdir admin data results reports misc manuscripts biblio conferences

All result and report files should be written under same format. Example: YYYY-MM-DD_tractoflow_output or YYYY-MM-DD_qc_rbx

To install ANTs, cmake must first be installed conda install cmake

It is then possible to use cmake to configure, build and install ANTs by running commands:

git clone https://github.com/ANTsX/ANTs.git
mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX=/opt/ANTs ../ANTs
make
cd ANTS-build
sudo make install

Assuming your install prefix was /opt/ANTs, there will now be a binary directory /opt/ANTs/bin, containing the ANTs executables and scripts.

export ANTSPATH=/opt/ANTs/bin/
export PATH=${ANTSPATH}:$PATH

Install Fsleyes as part of FSL or install with conda (with an independant environment) by typing: conda install -c conda-forge -n env_fsleyes fsleyes

To speed up the launching add alias to .bashrc: alias fsleyes="conda activate env_fsleyes && fsleyes"

Installation of dcm2bids can be done through conda (with new conda environment): conda install -c conda-forge -n env_dcm2bids dcm2bids

Also install dcm2niix with conda (same environmnent): conda install -c conda-forge dcm2niix

Create scaffolding with command: dcm2bids_scaffold

In code create configuration file with command: gedit dcm2bids_config.json

Installation of Datalad can be done with: sudo apt-get install datalad

The TemplateFlow Archive aggregates all the templates for redistribution. The archive uses DataLad to maintain all templates under version control.

• To install template flow with Datalad run command: datalad install -r ///templateflow. Usage example:

cd templateflow
datalad get -r tpl-MNI152NLin2009cAsym

• To install template flow with Python run command: python3 -m pip install templateflow Usage example:

from templateflow import api as tflow
tflow.get('MNI152NLin6Asym', desc=None, resolution=1, suffix='T1w', extension='nii.gz')

To execute a git pull from a different directory run command: git -C <git_dir> pull

Globus Connect Personal enables you to share and transfer files to and from your Linux laptop or desktop computer.

Open a terminal and find: cd globusconnectpersonal-x.y.z

Then run command: ./globusconnectpersonal

To install ANTs, cmake must first be installed conda install cmake

It is then possible to use cmake to configure, build and install ANTs by running commands:

mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX=/opt/ANTs ../ANTs
make
cd ANTS-build
sudo make install

Assuming your install prefix was /opt/ANTs, there will now be a binary directory /opt/ANTs/bin, containing the ANTs executables and scripts.

export ANTSPATH=/opt/ANTs/bin/
export PATH=${ANTSPATH}:$PATH

Install Fsleyes as part of FSL or install with conda (with an independant environment) by typing: conda install -c conda-forge -n env_fsleyes fsleyes

To speed up the launching add alias to .bashrc: alias fsleyes="conda activate env_fsleyes && fsleyes"

Installation of dcm2bids can be done through conda (with new conda environment): conda install -c conda-forge -n env_dcm2bids dcm2bids

Also install dcm2niix with conda (same environmnent): conda install -c conda-forge dcm2niix

Create scaffolding with command: dcm2bids_scaffold

In code create configuration file with command: gedit dcm2bids_config.json

The TemplateFlow Archive aggregates all the templates for redistribution. The archive uses DataLad to maintain all templates under version control.

• To install template flow with Datalad run command: datalad install -r ///templateflow. Usage example:

cd templateflow
datalad get -r tpl-MNI152NLin2009cAsym

• To install template flow with Python run command: python3 -m pip install templateflow Usage example:

from templateflow import api as tflow
tflow.get('MNI152NLin6Asym', desc=None, resolution=1, suffix='T1w', extension='nii.gz')

Neurodocker is a command-line program that generates custom Dockerfiles and Singularity recipes for neuroimaging. Neurodocker can be installed in a conda environment (using pip).

conda create -n neurodocker python pyyaml
conda activate neurodocker
python -m pip install neurodocker
neurodocker --help

To use neurodocker with singularity first create a .def file with command (example: Ants, Freesurfer, FSL)

neurodocker generate singularity \
--pkg-manager apt \
--base-image debian:stretch \
--ants version=2.3.2 \
--freesurfer version=7.3.1 \
--fsl version=6.0.5.1 \
> singularity_container

It is then possible to create a singularity image: sudo singularity build sing_container.sif singularity_container

La construction du container peut prendre plusieurs heures -- particulierement FSL step 2 (a roulé pendant 1 nuit entière). Maybe change export ANTSPATH="/opt/ants-2.3.2/" to export ANTSPATH="/opt/ants-2.3.2/bin/"

Singularity installation singularity build smriprep_img.simg docker://nipreps/smriprep

Download latest release from site. It is recommend using the *.rpm packages to install freesurfer on CentOS/RedHat linux, the *.deb package for Ubuntu and and the *.pkg installer for MacOS. To speed up, add to bashrc the FREESURFER_HOME env variable that freesurfer relies on:

alias setupfs='source $FREESURFER_HOME/SetUpFreeSurfer.sh'

Do not forget to export SUBJECTS_DIR before running freesurfer.

export SUBJECTS_DIR=/home/dev_tpil/freesurfer_results