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Basic tutorials (notebooks) and scripts for the lab

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Tutorials

All the tutorials are in jupyter notebook format.
You are welcome to update/improve previous tutorials or add your own one.

Launching

  • Click on the links with 🚀

  • Alternatively, go to Google Colab
    In Github section, print the repository's url:

https://github.com/Neuro-iX/Tutorials

Tutorial-1

🚀 New member's guidebook

Learning outcomes

  1. MonETS account setup
  2. Help updating Neuro-iX.github.io with your information
  3. New account to access Narval's compute nodes and Neuro-iX's Github
    a) Create an account on GitHub and Compute Canada Database (CCDB)
    b) Configure your ssh connexion to Narval cluster and GitHub repository
  4. Setup Miniconda, Git, Datalad and Jupyterlab on your laptop
    a) Understand Miniconda, Git, DataLad and JupyterLab
    b) Install Miniconda, Git, DataLad and JupyterLab
    c) Basics for Git, DataLad, JupyterLab and GitHub in bash
  5. Setup a virtual machine on your laptop
  6. Bonus: Some interesting applications and websites

Tutorial-2

🚀 Freesurfer

Learning outcomes

  1. Freesurfer overview
  2. Freesurfer installation/build
  3. Freesurfer tutorials
  4. Fastsurfer tutorials
    a) Fastsurfer overview
    b) Optional flags
  5. Nibabel: python library for neuro-images editing

Tutorial-3

🚀 Narval

Learning outcomes

  1. CCDB account setup and ssh connection to Narval
  2. Create a GLobus account for Data transfert (optional)
  3. Structure and Datasets in Narval
    a) Storage and file management on Narval
    b) Datasets in data
  4. Basic commands on a Narval node
  5. SLURM job templates
    a) Freesurfer 7.4.1 container
    b) Fastsurfer container

Tutorial-4

🚀 Lab computers

Learning outcomes

  1. Structure of office computers
  2. List of softwares installed
  3. List of softwares and some tips

Tutorial-5

🚀 Website

Learning outcomes

  1. Overview of Neuro-iX Website
  2. Install RStudio and some dependencies
  3. How to make changes and update

Tutorial-6

🚀 Publishing

Learning outcomes

  1. Submit an article on Arxiv
  2. Publish your code
    a) Clean code
    b) Docker image
    c) Boutique
    d) Nipoppy

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